GB2466988A

GB2466988A - Method for estimating reliability of a wireless network

Info

Publication number: GB2466988A
Application number: GB0900798A
Authority: GB
Inventors: Georgios Kalogridis
Original assignee: Toshiba Research Europe Ltd
Current assignee: Toshiba Europe Ltd
Priority date: 2009-01-19
Filing date: 2009-01-19
Publication date: 2010-07-21
Anticipated expiration: 2029-01-19
Also published as: GB2466988B; GB0900798D0

Abstract

One or more threats to the operation of a wireless communication network are analyzed with a view to determine rates of change, either in the threats, in associated threats or in a logical state of the wireless system. In particular, a predicted failure rate based on such indications is compared to a threshold level or to a repair rate at which the predicted failure rate exceeds the threshold or the repair rate. Information obtained may be used in predicting the future state of the wireless system or parts thereof and in aiding selection of reconfiguration and/or optimisation methods.

Description

METHOD AND APPARATUS FOR ESTIMATING RELIABILITY OF A WIRELESS

N ET\NORK

FIELD OF THE INVENTION

The present invention relates to wireless communication technology. In particular, the present invention relates to analysing treats to wireless communication networks and to estimating a network's reliability. Estimation results may be used to alter or optimise network performance.

BACKGROUND OF THE INVENTION

The use of networks operating according to the IEEE 802.11 standard has been increasing for some time. This increased use has given rise to concerns regarding the quality of service (QoS) provided by such networks, channel interference, and network load management, especially in densely populated areas, where channel scarcity increases co-channel and inter-channel interference.

The 2.4 GHz band for the IEEE 802.11 b/g standard designates 14 channels. Not all of these channels can, however, be utilised in all cases.

Regulations regarding the number of allowable channels or allowable channel power levels, for example, can differ between countries. In Japan, for example, all 14 channels can be used, while in the USA the use of only eleven channels is permitted. Some European countries only make 13 channels available, while in France channel usage is limited to four channels and in Spain to two channels.

Moreover for the 802.llb/g version of the standard, adjacent basic service sets (BSS)/access points (APs) have to be separated by five channels to prevent interchannel interference, as discussed by M. Gast in "802.11 Wireless Networks: The Definitive Guide", O'Reilly Media, Inc., 2005, the entirety of which is incorporated herein by this reference. For APs with overlapping coverage only three channels can consequently be used. The choice of alternative physical layers (PHY) within the 802.11 standard may have different limitations. For example, the 802.lla amendment of the standard specifies a PHY operating in 5.4 GHz, and offers 12 non-overlapping channels.

Channel scarcity resorts in either having no channel available for use for a new AP, or having increased interference. There are two main sources of interference: co-channel and interchannel interference. Interchannel interference occurs when there are overlapping channels. Co-channel interference is a result of overlapping cells that share the spectrum on the same channel.

To reduce interference between channels and/or to increase channel availability frequency planning schemes have been proposed. A typical frequency planning scheme for 802.11 b/g networks is illustrated in Figure 1.

Generally, there are a number of mechanisms available for optimising the resources of wireless links. Such optimisation mechanisms may, for example, focus on resource optimisation or protocol optimisation, or both, whereby both the algorithms and the frameworks used are attempted to be optimised. Some optimisation routines attempt to predict the future physical state of a channel so that the operating conditions of a wireless communication device or network utilising such a channel can be optimised to accommodate likely changes in the physical state of the channel.

S. Zhou and G. B. Giannakis disclose the use of adaptive protocols that attempt to predict the physical state of a channel in the form of Channel State Information (CSI) containing information characterising the wireless signal in "How accurate channel prediction needs to be for transmit-beamforming with adaptive modulation over Rayleigh MIMO channels?", Wireless Communications, IEEE Transactions on, vol. 3, pp. 1285-1294, 2004, the entirety of which is incorporated herein by this reference. This disclosure by Zhou and Giannakis is only one example of a large number of documents dealing with the prediction of future physical parameters of channels with a view to optimise channel use. The term channel modelling' has been used to describe the mechanisms that determine how the wireless signal propagates within a certain environment.

JP 2007-1 35207 discloses a deterministic model in which RF channels are chosen based on potential interfering signals.

US 2004/0142698 Al discloses a method of predicting future channel quality based on measurements of past and current channel quality. The predicted future channel quality is then used by a transmitter in updating transmission parameters.

US 6,687,239 Si discloses a method in which the performance of each channel is evaluated based on the occurrence of errors on the frequency channels used. If a predetermined quality criterion is not met the channel is substituted with a replacement channel.

Channel reliability schemes have also been proposed. One example of such a proposed scheme is D. Chen, S. Garg, C. Kintala, and K. S. Trivedi, "Dependability enhancement for IEEE 802.11 wireless LAN with redundancy techniques," Dependable Systems and Networks, 2003. Proceedings 2003 International Conference on, pp. 521-528, 2003, the entirety of which is incorporated herein by this reference. In this document the authors study a scenario in which the network scenario consists of overlapping cells, roaming nodes (i.e. mobility model) and a traffic model. The threat to the communication channel in this case is defined by nodes entering shadow regions.

D. Chen, S. Garg, and K. S. Trivedi further consider scenario where nodes in adjacent cells are linked through routers in "Network survivability performance evaluation: a quantitative approach with applications in wireless ad-hoc networks," Proceedings of the 5th ACM international workshop on Modelling analysis and simulation of wireless and mobile systems, pp. 61-68, 2002, the entirety of which is incorporated herein by this reference. A number of communication threats, such as link faults and router failures, are considered in this context.

The paper "Survivability Analysis of Ad Hoc Wireless Network Architecture" by K. Paul, R. RoyChoudhuri, and S. Bandyopadhyay published in Mobile and Wireless Communications Networks: lFlP-TC6/European Commission Networking 2000 International Workshop, MWCN 2000: Paris, France, May 16-17, 2000: Proceedings, 2000, the entirety of which is incorporated herein by this reference, studies a multi-hop connectivity scenario where nomadic mobile nodes may loose end-to-end connectivity when there is no route to connect two nodes or when a link breaks due to collisions.

SUMMARY OF THE INVENTION

According to an aspect of the present invention there is provided an apparatus for evaluating a communication threat to a wireless network. The apparatus is arranged to obtain an indication, for example a quantitative indication, of one or more communication threats affecting the wireless network and to dynamically calculate based on said indication a failure rate at which the communication threat to which the indication relates, or an associated communication threat, transitions from a level below a predetermined threshold to a level above the threshold and/or a repair rate at which the communication threat to which the indication relates, or the associated communication threat, transitions from a level above the predetermined threshold to below the predetermined threshold. The present invention thus considers factors that can threaten communication in a wireless system and attempts to predict a future state based on these factors. In this instance the invention attempts to predict the likelihood of the threat to which the indication relates or of the associated threat existing in a particular form, that is at a level above the threshold level.

The threshold level may be chosen based on knowledge that the threat may become particularly detrimental if it reaches such a level/intensity. This way of considering threats to the wireless network system can be considered as analysing a threat as a birth/death process, with the threat being considered as effectively coming into existence when it first exceeds the threshold and to cease existing when its intensity falls below the threshold.

The type of indication obtained may depend on the nature of the threat it relates to. It is envisaged that for some types of threat a quantitative indication of the current level of the threat is required to appropriately express the threat for further analysis. Other types of threat may be sufficiently characterised by an indication of the presence or absence of the threat.

The present invention is, however, not limited to considering a particular threat and to then determining failure and repair rates for this particular threat.

Instead the present invention also extends to obtaining information regarding one or more threats and to then determine the failure and/or repair rates of a further threat associated with the one or more quantified threats, thus providing the basis for making predictions regarding the likely existence or absence of a threat that may not be directly or easily quantifiable.

The present invention moreover recognises that the determined failure/repair rates may become outdated, for example when the channel's operating context changes in a manner that may negatively affect the channel's ability to support a basic service set. For this reason the present invention in this aspect determines the rates dynamically so that channel optimisation routines or survivability measures that may be invoked based on the determined rates benefit from up to date and correct information.

It will of course be appreciated that a large number of threats can affect a wireless network. An indication of more than one communication threat may thus be obtained and a plurality of failure and/or repair rates may be calculated.

One repair rate may be calculated for each of the threats and/or one failure rate may be calculated for each of the threats.

The present invention is moreover not limited to predicting failure and/or repair rates of threats alone. In another aspect of the invention information, such as quantitative information, relating to one or more threats that may potentially affect a wireless network may be used to form the basis for predicting a likely future logical state of the wireless network, or of parts thereof.

This has been recognised as being advantageous in its own right and according to another aspect of the present invention there is thus provided an apparatus for evaluating communication threats to a wireless network, the apparatus arranged to obtain an indication, such as a quantitative indication, of one or more communication threats affecting the wireless network and to dynamically calculate, based on said indication, a failure rate at which the wireless network or one or more parts of the wireless network transition from a current logic state to another logic state or a repair rate at which the wireless network or one or more parts of the wireless network transition from a logic state other than the current logic state to the current logic state.

The apparatus may further be arranged to use the determined rates (be that failure/repair rates of a threat or of a logical status) to predict the reliability of the wireless network or one or more parts thereof, such as one or more communication channels. The apparatus may, for example, be arranged to calculate a probability of a wireless communication channel having a predetermined state at a predetermined point of time. The probability may be the probability of the channel remaining in the present state until the predetermined point in time. Alternatively or additionally an expected period of time over which a wireless communication channel is likely to remain in a present state may be calculated.

More generally, the apparatus may be arranged to predict a future logical state of the wireless network or a communication channel thereof at a predetermined time in the future based on the determined rate or rates. An example of the prediction of such a future logical state may be to predict the likely number of channels available for participation in the wireless network at a point of time in the future. The apparatus may predict the reliability or the future logical state based on a model modified based on the rate or rates.

Once a prediction of the future state of for example the network or a channel has been made the prediction may be used to implement optimisation measures with a view to improve the performance of the wireless network. The apparatus may be arranged to select one or more optimisation measures from among a number of available optimisation measures based on the prediction for this purpose. The derived information may also be used in configuring a reliability model that may find use in survivability decision making.

The above discussion focuses on the analysis of threats. Such threats may be, for example, traffic congestion, co-channel interference, inter-channel interference, deterioration in channel quality, interference/interference pattern on the channel, device mobility, channel noise and deteriorating signal amplitude to name a few. The present analysis may additionally take other factors into account that do not necessarily pose a threat to the reliability of the network but that may nevertheless modulate its performance. Such other factors may for example relate to information relating to the context of the operation of the wireless network, or parts thereof.

Known ways of considering channel properties attempt to measure current radio propagation parameters, for example by transmitting test data via the wireless connection with the objective of quantifying path loss along a wireless communication link/channel and to predict the area of coverage of the link. In such known methods a channel is defined as the physical transmission medium between a transmitter antenna and a receiver antenna, all materials surrounding this medium, the topology of these materials and the dynamic changes that may occur to such topology, for example due to movement of the transmitter and/or receiver antenna. It is proposed that the inclusion of the above mentioned other factors goes beyond these known ways of considering channel quality. In particular the inclusion of the above mentioned other factors may consider a channel as a path that connects a data source to a data sink.

This path may comprise a physical channel in the sense used in known methods but is further defined by the way this path appears to the data source/data sink. A thus defined channel could for example be the medium that is used by the Medium Access Control layer (MAC) for transmitting packets or the medium that a Link-Layer API provides to higher layers in the OSI system.

One way of distinguishing factors relating to known ways of evaluating channel properties is to consider them as being determinable based on information derivable from the physical layer of the OSI model only. It is envisaged that information included in the present consideration is information that is instead derivable from the link layer of the OSI model or layers above the link layer.

Mechanisms for measuring and reporting such more general context information include those provided by the 802.11k standard (IEEE, "IEEE Standard for Information technology -Telecommunications and information exchange between systems -Local and metropolitan are networks -Specific requirements Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) specifications Amendment 1: Radio Resource Measurement of Wireless LANs," Institute of Electrical and Electronics Engineers, 2007, the entirety of which is incorporated herein by this reference), which enables radio resource and performance measurement protocols among network nodes. The pre-standardisation GOLLUM project (T. Farnham, A. Gefflaut, A. Ibing, P. Maehoenen, D. Melpignano, J. Riihijaervi, and M. Sooriyabandara, "Toward Open and Unified Link-Layer API," Proceedings of the 1ST Mobile and Wireless Summit, 2005, the entirety of which is incorporated herein by this reference) moreover specifies an application programming interface (API) to enable the intelligent measurement and gathering of link layer attributes. These attributes may be used as input channel context information in determining the channel reliability parameters.

The dynamic calculation may not be performed continuously. Instead the apparatus may be arranged to only perform the dynamic calculation only following a detected change in the level of the one or more threats. Postponing computation in this manner until after a change in the level of one or more threats has been detected allows reducing the amount of computational resource required while ensuring that the determined rates are up to date at all times. In one arrangement the dynamic calculation is only performed once it has been established that the level of the communication threat has changed from within a first predetermined parameter range to within a second predetermined parameter range. The predetermined parameter ranges may be defined based on prior knowledge of the significance of a threat and may be designed such that the boundary or boundaries of two parameter ranges are such that, if the level of the threat crosses the boundary or boundaries, the change in the threat will have an appreciable effect on the calculated failure/repair rates of the threat, the associated threat and/or the logical state.

This may be advantageous in cases where it is known that small changes in a threat level do not lead to appreciable or significant changes in the calculated rates. Further reductions in the amount of computational resources required for computing the rates can therefore be achieved.

The apparatus may form part of an application program interface (API) that is arranged to provide a communication medium to OSI layers higher than the link layer. An API of this nature can obtain qualitative and quantitative information regarding a threat or threats as well as information relating to the operating context of the wireless network or parts thereof, such as network channels. The API may be arranged to access link-layer information.

The present invention also extends to wireless devices including one of the above discussed apparatus. Such wireless devices may be laptops, mobile phones, access points or other wireless infrastructure systems or back-up systems.

According to another aspect of the present invention there is provided a method of evaluating communication threats to a wireless network comprising obtaining an indication of one or more communication threats acting on the wireless network and dynamically calculating based on said indication a failure rate at which the communication threat or an associated communication threat transitions from a level below a predetermined threshold to a level above the threshold and/or a repair rate at which the communication threat or the associated communication threat transitions from a level above the predetermined threshold to below the threshold.

According to another aspect of the present invention there is provided a method of evaluating communication threats to a wireless network comprising obtaining an indication of one or more communication threats acting on the wireless network and dynamically calculating based on said indication a failure rate at which the wireless network or one or more parts of the wireless network transitions from a current logic state to another logic state or a repair rate at which the wireless network or one or more parts of the wireless network transitions from a logic state other than the current logic state to the current logic state.

BRIEF DESCRIPTION OF THE DRAWINGS

Figure 1 shows a typical frequency planning scheme for 802.llb/g networks; Figure 2 shows one exemplary arrangement incorporating a preferred embodiment of the present invention; Figure 3 illustrates a number of the contextual parameters that can define a communications network; Figure 4 shows a model illustrating the failure and repair of wireless channel; Figure 5 is a black box illustration of an exemplary channel reliability parameter estimator; Figure 6 shows a steady state channel model.

DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS

Figure 2 shows an optimisation system 10 incorporating an embodiment of the present invention. In the arrangement shown in Figure 2 a number of threats 20 that may potentially affect the operation or reliability of the wireless network optimised by the optimisation system 10 are acquired as an input of the optimisation system 10. Other contextual parameters may also be input into the optimisation system 10. Input parameters for a channel reliability parameter estimator 40 (referred to in short as X-estimator 40 in the following) are then created based on these input threats 20 and/or the other contextual parameters that may affect the channels under consideration. X-estimator 40 is arranged to compute a failure rate at which one or more of the communication threats transitions from an acceptable level below a predetermined threshold to an unacceptable level above the threshold. Alternatively or additionally the X-estimator 40 may compute a repair rate at which one or more of the communication threats transitions from an unacceptable level above a predetermined threshold to an acceptable level below the threshold. This increase and decrease of the significance of a threat can be considered as a birth/death process of the threat. The operation of 40 will be discussed in more detail and by way of example below.

The failure/repair rates calculated by the X-estimator 40 form the input to the channel reliability predictor 50 (referred to in short as R-predictor 50 in the following). The R-predictor conducts a probabilistic analysis of the threats based on the input from the ?-estimator 40 and in one arrangement calculates values indicating the likely time over which a channel in question or parts or all of the wireless network will remain in a reliable state, for example a state in which the channel, the part of the network or the entire network will be able to reliably transmit data according to the requirements of the network. The calculations of the R-predictor are based on the rates supplied by the X-estimator 40. The R-predictor 50 may form a steady-state model of the threats influencing the wireless network, of the logical states of the wireless network or channel conditions. This model is modified by the input received from the -estimator 40.

Based on the output of the R-predictor 50 a decision making unit 60 can then determine whether the framework of the network or the algorithms used for operating the network need to be altered in order to improve the transmission quality or reliability of the network. Such alterations and optimisations may apply to the entirety of the network or only to parts of it, such as for example one or more channels.

In one embodiment the ?-estimator 40 and the R-predictor 50 form plug-ins within a framework that provides an application program interface (API) through which indications of the presence, absence and/or strength of a threat as well as other channel context information can be derived and analysed if required. The output of the R-predictor 50 may then be used in the context of the API as the basis for a decision making process, for example to reduce the danger of data loss or communication interruption.

Figure 3 illustrates a number of the contextual parameters that can define a communications network including the communications options, targets and threats indicated. The data input to the ?-estimator 40 may be based on a number of such threat, or on a combination of threats and contextual parameters. It is emphasised that such context information relates to the context in which the network is operated, such as link layer information, rather than the physical parameters describing channel performance. Context information of this type can, for example, be acquired from the unified Link-layer API (ULLA) proposed as part of the GOLLUM project in 1. Farnham, A. Gefflaut, A. Ibing, P. Mähönen, D. Melpignano, J. Riihijärvi, and M. Sooriyabandara, "Toward Open and Unified Link-Layer API," Proceedings of the 1ST Mobile and Wireless Summit, 2005, the entirety of which is incorporated herein by this reference.

Discussing in the following the operation of the ?-estimator 40 and of the R-predictor 50 in more detail and by way of example only, the A'-estimator 40 calculates failure and repair rates of communication threats as shown in Figure 4. Figure 4 shows two states of the threat. In a first state 100 the level of the threat is below a predetermined threshold, in the second state above it. The threat may be considered as coming into existence or ceasing to exist when transitioning from below the threshold to above the threshold or vice versa. The rate at which a threat transitions from state 100 to state 110 will be referred to as failure rate 2. The rate at which the threat transitions from state 110 to state will be referred to as repair rate r1. These rates may be considered sub-models that can be used in predicting communication threats. In particular, the X-estimator 40 is used to convert a particular current level of a communication threat into a value or values, namely the above discussed rates, that are more useful in predicting system reliability. The repair and failure rates calculated by the X-estimator 40 may directly relate to the current threat information input to the estimator 40. In other words, some of the repair and failure rates computed by the ?-estimator 40 may be rates at which an input threat comes into existence or ceases to exist. The ?-estimator 40 can moreover compute repair and failure rates of communication threats that cannot be directly or easily quantified and that cannot accordingly easily be provided to the X-estimator 40 in the form of an input value. Determination of such rates may be based on, for example, a known interaction of available input threats forming such additional threats. Additionally or alternatively the X-estimator 40 may determine a rate of transition of the network or part of it between logical states of the network.

Figure 5 is a black box illustration of an exemplary ?-estimator 40. The AS-estimator 40 receives input values C and computes output reliability parameters A. As discussed above, the input values C relate to information on communication threats, possibly in conjunction with channel context information. The output channel reliability parameters A contain repair rates r1 or/and failure rates A required by the R-predictor for predicting the reliability of the system or of parts of the system, such as one or more channels. The reliability parameters A are calculated dynamically by the 2-estimator 40, so that the reliability parameters A accurately reflect the likely repair rates i or failure rates 2 that will be experienced in use. In one arrangement this computation may be continuous. However, in a less computationally demanding examples the 2-estimator 40 only computes updated reliability parameters A upon detecting a change in the input information C. It may also be assumed in one arrangement that small changes in the input information C are unlikely to alter the parameters A appreciably. A component C of C may be able to take a range of values [c0:C,Nj, wherein this range is divided into a number of sub-ranges. These sub-ranges can be such that a change within a sub-range does not cause a change in the parameters A that is sufficiently large to appreciably or significantly alter the performance of the channel. As a consequence the parameters A may only be calculated if the value C1 changes from one sub-range to another. It will be appreciated that an arrangement of this type reduces the number of times the parameters A need to be calculated, thereby reducing the overall amount of computational resources expended on the computation.

The parameters A computed by the X-estimator 40 form the input for the R-predictor 50. The R-predictor uses a reliability model to dynamically predict the future reliability of a channel based on the parameters A, be that at one or at more than one specific points in the future. This reliability model may be dynamically reconfigured to account for changes in the parameters A These predictions of the R-predictor 50 can then be used in real-time optimisation and reconfiguration of the communication system or parts thereof in light of changes in the communication threats. The R-predictor 50 may moreover make a recommendation as to which of a number of available optimisation and reconfiguration options could or should be adopted in view of the parameters A or changes therein. Implementation of any reconfiguration or optimisation measures that may have been chosen based on such a recommendation does not fall within the functions of the R-predictor, although it is envisaged that the R-predictor or the combination of the ?-estimator and the R-predictor may form part of an apparatus governing the operation of a communication system. Any such optimisation steps may, for example, form part of survival optimisation offering a solution in situations where other known optimisation steps fail to maintain good levels of network and/or application survivability.

An example of an optimisation of the communication system is the re-allocation of a communication channel to a more reliable frequency. In the case of a system using dynamic channel allocation the R-predictor can, for example, calculate the probability that a certain channel will fail to support a certain BSS within the next t seconds, or within future time frame [ti, t2]. Alternatively or additionally it could be predicted that an amount of interference will likely be encountered that will likely cause the QoS requirements of a scheduled application to not be fulfilled. The R-predictor may additionally or alternatively predict the probability that a channel will repair itself for a certain BSS within the next t seconds or within future time bracket [ti, t2]. It may, for example, be predicted that the channel will be sufficiently interference-free to support scheduled or expected/predicted traffic requirements. It will be appreciated that the combination of the A-estimator 40 and the R-predictor 50 can be seen as a control system with feedback, since the output A of the A-estimator 40 will have an impact on the input C. The objective of this control system is the minimisation of communication threats within C, or else the maximisation of the reliability of the channel.

It is in the following assumed that a set of threats C input to the A-estimator 40 is linked with a logical state of the system in a manner that any set C is uniquely mapped to a system state according to: (C), where S is an enumerator of the logical state of the system. The R-predictor 50 can be designed so that this assumption is true. Over a certain length of time, t, a family of sets C, Cr(C), can be obtained from the channel. Based on this information the total time the system has existed in each state S, before transitioning to another state S during the period t can then be calculated using: (s) (1) where ( C),J) is the duration the system has existed in the state S, before transiting to the state S, when a certain set C was in use. Equation (1) is a good approximation of the statistical mean time for which the system will stay in the corresponding state S,, if the interval t is chosen to be big when compared to all r(5). The mean time for which the state S will exist before transiting to a state S1 during the period t is: MT.BF = ir(5LJ) where MTBF is the mean time before a particular failure of the system from state S, to state S1, Based on this and the standard theory of reliability A (which represents a constant rate) can now be calculated using: = MTBF More generally, the A-estimator can calculate all failure/repair rates based on: 1 (2) -(sw) -Ic (C)i(t(Ci ij) Following an initial training period t in which data can be obtained, smoothed running estimates of the time a channel can be expected to remain in a state S1 before transiting to a state S can be calculated as such: (s..) = (s. .)+ 1+1.J smoothed i where L,(S1) is a previously determined total time the system has existed in the state S, before transitioning to state S1, +1(s) is a more recently determined total time the system has existed in the state S, before transitioning to state S, and a is a smoothing factor. The total time the system has existed in the state S, before transitioning to state S1 that may be used for further calculations is the smoothed total time A (s. .) 1+ j,J smoothed Having all the set of values of i, the R-predictor 50 can now calculate the probability that the system or the part of it will transit from the state S, to the state S1 within the next t1 seconds according to: R(t1)= e" It will be appreciated that the above example relates to one specific manner in which reliability parameters can be determined and used for estimating the duration over which the system is likely to remain in the specific state. The present invention is by no means limited to this specific example and other ways of dynamically calculating reliability parameters and the reliability of a communication system are also envisaged.

As an example, consider that at time t there is the following set of threat indexes: C{C1, C2, ..., C22}, where C1 C11 indicate the threat level due to increasing traffic load in channels 1-11, and C12 -C22 indicate the threat level due to signal quality mitigation (affected by both distance from access point and noise, interchannel interference, etc) in channels 1-1 1. The following notation is adopted for the channels within an operating region of a BSS. The total number of available channels is N. If at a certain time k channels are usable in the region (N-k) channels are unusable, then the BSS can be said to be in a state Sk1. S, thus represents the number of channels the BSS cannot use and it is not related to the physical channel numbers that are associated with the current frequency the BSS operates on. A state S1 fails with a rate A, and it is repaired with a rate r,. When a state fails, the BSS will have to be reconfigured. Such reconfiguration brings about a delay o, which may, if the reconfiguration for example consists of re-allocating resources from a failed channel to a functioning channel, consist of the time required for scanning for another channel, broadcast connection details to the nodes involved and perform the actual re-allocation of the channel. Figure 6 illustrates the manner in which a system transitions between the above defined states.

The system states S1 can be designed so that current threats levels are mapped to them. For example, consider that in time t the threats Ci -C8, and C12 -C19 are above the threshold that makes a real time video transmission unreliable (e.g. increased data loss, increased delay and increased video jitter).

This means that at the current time t there are three channels (9, 10 and 11) which seem to have acceptable threat levels and are, thus, suitable. As such, we consider the system to exist in state Sk1 = S2. In one arrangement the values A1 and r1 are dynamically calculated and updated by the A-estimator 40, based on the input values C by using equation (2) above.

The combination of the proposed A-estimator and R-predictor can be used for dynamically adapting a reliability model to the changes occurring within a wireless channel in order to provide sound calculations of future threats to communication. Based on these calculations proactive steps can be taken with a view to minimise the risks and increase the overall reliability of communications.

Claims

CLAIMS: 1. An apparatus for evaluating communication threats to a wireless network, the apparatus arranged to: obtain an indication of one or more communication threats affecting the dynamically calculate based on said indication a failure rate at which the communication threat or an associated communication threat transitions from a level below a predetermined threshold to a level above the threshold and/or a repair rate at which the communication threat or the associated communication threat transitions from a level above the predetermined threshold to below the threshold.
2. An apparatus according to Claim 1, wherein a quantitative indication of more than one communication threat is obtained and wherein a plurality of failure and/or repair rates are calculated.
3. An apparatus according to Claim 2, wherein one repair rate is calculated for each threat.
4. An apparatus according to Claim 2 or 3, wherein one failure rate is calculated for each threat.
5. An apparatus for evaluating communication threats to a wireless network, the apparatus arranged to: obtain an indication of one or more communication threats affecting the dynamically calculate based on said indication a failure rate at which the wireless network or one or more parts of the wireless network transitions from a current logic state to another logic state or a repair rate at which the wireless network or one or more parts of the wireless network transitions from a logic state other than the current logic state to the current logic state.
6. An apparatus according to any preceding claim, further arranged to predict the reliability of said wireless network or one or more parts thereof based on said rate or rates.
7. An apparatus according to Claim 6, wherein a said one or more parts of the wireless network are one or more communication channels.
8. An apparatus according to Claims 6 or 7, the apparatus arranged to make said prediction based on a steady-state model.
9. An apparatus according to any of Claims 1 to 5, further arranged to predict a future logical state of the wireless network or a communication channel thereof at a predetermined time in the future based on said rate or rates.
10. An apparatus according to any of Claims 6 toY the apparatus further arranged to predict said reliability or said future logical state based on a model, wherein said model is modified based on said rate or rates,
11. An apparatus according to any of Claim 6 to 10, further arranged to select one or more optimisation measures from among a number of available optimisation measures based on said prediction.
12. An apparatus according to Claim 11, further arranged to determine a likely future logical state of the wireless network based on a said selected optimisation measure.
13. An apparatus according to any preceding claim, arranged to perform said dynamic calculation only following a detected change in the level of the one or more threats.
14. An apparatus according to Claim 13, arranged to perform said dynamic calculation when a said communication threat changes from within a first predetermined parameter range to within a second predetermined parameter range.
15. An apparatus according to any preceding claim, further comprising an application program interface (API) arranged to provide a communication medium to OSI layers higher than the link layer.
16. An apparatus according to Claim 15, wherein the API is arranged to access link-layer information.
17. A wireless device comprising an apparatus according to any preceding claim.
18. A wireless device as claimed in Claim 17, wherein said wireless device is a laptop, a mobile phone or an access point.
19. A method of evaluating communication threats to a wireless network comprising: obtaining an indication of one or more communication threats acting on the wireless network; and dynamically calculating based on said indication a failure rate at which the communication threat or an associated communication threat transitions from a level below a predetermined threshold to a level above the threshold and/or a repair rate at which the communication threat or the associated communication threat transitions from a level above the predetermined threshold to below the threshold.
20. A method according to Claim 19, wherein said step of obtaining a quantitative indication comprises obtaining a quantitative indication of more than one communication threat and further comprising calculating a plurality of failure and/or repair rates.
21. A method according to Claim 20, wherein one repair rate is calculated for each threat.
22. A method according to Claim 20 or 21, wherein one failure rate is calculated for each threat.
23. A method of evaluating communication threats to a wireless network comprising: obtaining a quantitative indication of one or more communication threats acting on the wireless network; and dynamically calculating based on said indication a failure rate at which the wireless network or one or more parts of the wireless network transitions from a current logic state to another logic state or a repair rate at which the wireless network or one or more parts of the wireless network transitions from a logic state other than the current logic state to the current logic state.
24. A method according to any of Claim 19 to 23, further comprising predicting the reliability of said wireless network or one or more parts thereof based on said rate or rates.
25. A method according to Claim 24, wherein a said one or more parts of the wireless network are one or more communication channels.
26. A method according to any of Claims 19 to 25, further comprising predicting a future logical state of the wireless network or a communication channel thereof at a predetermined time in the future based on said rate or rates.
27. A method according to any of Claims 24 to 26, further comprising predicting said reliability or said future logical state based on a model and modifying said model based on said rate or rates.
28. A method according to any of Claim 24 to 27, further comprising selecting one or more optimisation measures from among a number of available optimisation measures based on said prediction.
29. A method according to any of Claim 19 to 28, further comprising performing said dynamic calculation only following a detected change in the level of the one or more threats.
30. A method according to Claim 29, further comprising performing said dynamic calculation when a said communication threat changes from within a first predetermined parameter range to within a second predetermined parameter range.