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Multicast is an efficient paradigm for transmitting data from a sender to a group of receivers. In this paper, we focus on multicast in single channel multi-access wireless local area networks (LANs) comprising several small cells. In such a system, a receiver cannot correctly receive a packet if two or more packets are sent to it at the same time, because the ackets "collide". Therefore, one has to ensure that only one node sends at a time. We look at two important issues.First, we consider the problem of the sender acquiring the multi-access channel for multicast transmission. Second, for reliable multicast in each cell of the wireless LAN, we examine ARQ-based approaches. The second issue is important because the wireless link error rates can be very high. We present a new approach to overcome the problem of feedback collision in single channel multi-access wireless LANs, both for the purpose of acquiring the channel and for reliability. Our approach involves the election of one of the multicast group members (receivers) as a "leader" or representative for the purpose of sending feedback to the sender. For reliable multicast, on erroneous reception of a packet, the leader does not send an acknowledgment, prompting a retransmission. On erroneous reception of the packet at receivers other than the leader, our protocol allows negative acknowledgments from these receivers to collide with the acknowledgment from the leader,thus destroying the acknowledgment and prompting the sender to retransmit the packet. Using analytical models, we demonstrate that the leader-based protocol exhibits higher throughput in comparison to two other protocols which use traditional delayed feedback-based probabilistic methods. Last, we present a simple scheme for leader election.

We model the spread of information in a homogeneously mixed population using the Maki Thompson rumor model. We formulate an optimal control problem, from the perspective of single campaigner, to maximize the spread of information when the campaign budget is fixed. Control signals, such as advertising in the mass media, attempt to convert ignorants and stiflers into spreaders. We show the existence of a solution to the optimal control problem when the campaigning incurs non-linear costs under the isoperimetric budget constraint. The solution employs Pontryagin's Minimum Principle and a modified version of forward backward sweep technique for numerical computation to accommodate the isoperimetric budget constraint. The techniques developed in this paper are general and can be applied to similar optimal control problems in other areas. We have allowed the spreading rate of the information epidemic to vary over the campaign duration to model practical situations when the interest level of the population in the subject of the campaign changes with time. The shape of the optimal control signal is studied for different model parameters and spreading rate profiles. We have also studied the variation of the optimal campaigning costs with respect to various model parameters. Results indicate that, for some model parameters, significant improvements can be achieved by the optimal strategy compared to the static control strategy. The static strategy respects the same budget constraint as the optimal strategy and has a constant value throughout the campaign horizon. This work finds application in election and social awareness campaigns, product advertising, movie promotion and crowdfunding campaigns., Comment: Accepted for publication in Communications in Nonlinear Science and Numerical Simulation

We consider a structured sensor network in which sensors and relays are arranged in a regular grid. Sources S1, S2, ..., SK are located sequentially at the top row, and destinations D1, D2, ..., DK are arranged in an arbitrary order at the bottom row; data from Si is required at Di. Such networks serve as models for planned sensor deployments (for example, sensors deployed in a precision agriculture project). Nodes have limited energy, and our objective is to maximize the aggregate bits transported from source(s) to destination(s) before network partition. In contrast to formulations that seek to optimize either the network lifetime or the throughput, our criterion considers both aspects; the criterion is natural and novel. We show that our problem can be converted to a Linear Program. Next, we move on to consider relay nodes that not only forward data but are also capable of XOR-ing received packets. We study how this “coding capability” can be leveraged to improve the performance objective. We provide an algorithm that chooses the optimal number of coding points. Finally, we evaluate the additional benefit that XOR-ing can yield. For this evaluation, we formulate an optimization problem using “functional flow conservation.” Two XOR-ed packets get “fused” to one, because of which, at the coding points, the usual flow conservation notion does not apply; hence the need for functional flow conservation. We propose functional flow equations for directed acyclic graph networks; this is novel, as the current literature considers only tree graphs. Our results indicate that the gain in bits transported can be as much as 83%.

We consider a problem of admission control to a single queue in discrete time. The controller has access to k-step old queue lengths only, where k can be arbitrary. The problem is motivated, in particular, by recent advances in high-speed networking where information delays have become prominent. We formulate the problem in the framework of Completely Observable Controlled Markov Chains, in terms of a multi-dimensional state variable. Exploiting the structure of the problem, we show that under appropriate conditions, the multi-dimensional Dynamic Programming Equation (DPE) can be reduced to a unidimensional one. We then provide simple computable upper and lower bounds to the optimal value function corresponding to the reduced unidimensional DPE. These upper and lower bounds, along with a certain relationship among the parameters of the problem, enable us to deduce partially the structural features of the optimal policy. Our approach enables us to recover simply, in part, the recent results of Altman and Stidham, who have shown that a multiple-threshold-type policy is optimal for this problem. Further, under the same relationship among the parameters of the problem, we provide easily computable upper bounds to the multiple thresholds and show the existence of simple relationships among these upper bounds. These relationships allow us to gain very useful insights into the nature of the optimal policy. In particular, the insights obtained are of great importance for the problem of actually computing an optimal policy because they reduce the search space enormously.

We present a centralized integrated approach for: 1) enhancing the performance of an IEEE 802.11 infrastructure wireless local area network (WLAN), and 2) managing the access link that connects the WLAN to the Internet. Our approach, which is implemented on a standard Linux platform, and which we call ADvanced Wi-fi Internet Service EnhanceR (ADWISER), is an extension of our previous system WLAN Manager (WM). ADWISER addresses several infrastructure WLAN performance anomalies such as mixed-rate inefficiency, unfair medium sharing between simultaneous TCP uploads and downloads, and inefficient utilization of the Internet access bandwidth when Internet transfers compete with LAN-WLAN transfers, etc. The approach is via centralized queueing and scheduling, using a novel, configurable, cascaded packet queueing and scheduling architecture, with an adaptive service rate. In this paper, we describe the design of ADWISER and report results of extensive experimentation conducted on a hybrid testbed consisting of real end-systems and an emulated WLAN on Qualnet. We also present results from a physical testbed consisting of one access point (AP) and a few end-systems.

Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an "adaptive threshold," i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

In this paper we present the design of "e-SURAKSHAK," a novel cyber-physical health care management system of Wireless Embedded Internet Devices (WEIDs) that sense vital health parameters. The system is capable of sensing body temperature, heart rate, oxygen saturation level and also allows noninvasive blood pressure (NIBP) measurement. End to end internet connectivity is provided by using 6LoWPAN based wireless network that uses the 802.15.4 radio. A service oriented architecture (SOA) [1] is implemented to extract meaningful information and present it in an easy-to-understand form to the end-user instead of raw data made available by sensors. A central electronic database and health care management software are developed. Vital health parameters are measured and stored periodically in the database. Further, support for real-time measurement of health parameters is provided through a web based GUI. The system has been implemented completely and demonstrated with multiple users and multiple WEIDs.

As migration to IPv6 occurs slowly, IPv4 and IPv6 hosts will coexist for many years. We consider a specific scenario where the legacy IPv4 systems can not be upgraded and also the new systems are IPv6. The mix of IPv4 and IPv6 machines exist in the same network and both need to interoperate. We propose a novel Translator called SBIIT (Socket identifier Based IPv4/IPv6 Translator), which is based on a modification of NAT-PT. SBIIT provides support for SIP, SAP and multicast translation. To do this, translation has to be performed in packet headers as well as in payloads, because these protocols embed IP addresses in payloads. Moreover, this is achieved without any modifications to v4/v6 end hosts. We design and implement SBIIT in hardware using the network processor IXP 435 from Intel. Extensive tests demonstrate that the Translator is able to provide seamless interoperability between v4 and v6 hosts running applications based on SIP, Multicast, TCP, UDP as well as ICMP.

Performance analysis of TCP-controlled long file transfers in a WLAN in infrastructure mode is available in the literature with one of the main assumptions being equal window size for all TCP connections. In this paper, we extend the analysis to TCP-controlled long file uploads and downloads with different TCP windows. Our approach is based on the semi- Markov process considered in [1] and [2], but with arbitrary window sizes. We present simulation results to show the accuracy of the analytical model.

Achieving optimal transmission throughput in multi-hop wireless networks is a fundamental but hard problem. The situation is aggravated when nodes are mobile. Further, multi-rate systems make the analysis of throughput more complicated. In mobile scenario, a link may break or be created as nodes are moving within communication range. ‘Route and schedule discovery’ which is to find the optimal route and transmission schedule is an important issue. Route and schedule discovery entails some cost; so one would not like to initiate discovery too often. On the other hand, not discovering reasonably often entails the risk of being stuck with a suboptimal route and/or schedule, which hurts end-to-end throughput. The implementation of the routing decision problem in one dimensional mobile ad hoc network as Markov decision process problem is already discussed in [1]. A heuristic based on threshold policy was presented in the same paper without giving a way to find the threshold. In this paper, we suggest a rule for setting the threshold, given the parameters of the system. We also point out that our results remain valid in a slightly different mobility model; this model is a first step towards an ‘open’ network in which existing relay nodes can leave and/or new relay nodes can join the network.

We analyze TCP-controlled bulk file transfers in a single station WLAN with nonzero propagation delay between the file server and the WLAN. Our approach is to model the flow of packets as a closed queueing network (BCMP network) with 3 service centres, one each for the Access Point and the STA, and the third for the propagation delay. The service rates of the first two are obtained by analyzing the WLAN MAC. Simulations show a very close match with the theory.

In this paper, we consider the problem of modelling the average delay experienced by an application packets of variable length in a single cell IEEE 802.11 DCF wireless local area network. The packet arrival process at each node i is assumed to be a stationary and independent increment random process with mean a i and second moment a i (2). The packet lengths at node i are assumed to be i.i.d random variables P i with finite mean and second moment. A closed form expression has been derived for the same. We assume the input arrival process across queues to be uncorrelated Poison processes. As the nodes share a single channel, they have to contend with one another for a successful transmission. The mean delay for a packet has been approximated by modelling the system as a 1-limited Random Polling system with zero switchover times. Extensive simulations are conducted to verify the analytical results.

Several users share a common channel for transmission, which has an average rate constraint. The packets not yet transmitted are queued. The problem of optimal channel allocation to minimize the average sum queue occupancy subject to this constraint splits into individual Markov decision processes (MDPs) coupled through the Lagrange multiplier for the rate constraint. This multiplier can be computed by an on-line stochastic gradient ascent in a centralized or distributed manner. This gives a stochastic dynamic version of Kelly’s decomposition. A learning scheme is also presented.

In this paper, we consider the problem of modelling the average delay in an IEEE 802.11 DCF wireless mesh network with a single root node under light traffic. We derive expression for mean delay for a co-located wireless mesh network, when packet generation is homogeneous Poisson process with rate \lambda. We also show how our analysis can be extended for non-homogeneous Poisson packet generation. We model mean delay by decoupling queues into independent M/M/1 queues. Extensive simulations are conducted to verify the analytical results.

We focus on the energy spent in radio communication by the stations (STAs) in an IEEE 802.11 infrastructure WLAN. All the STAs are engaged in web browsing, which is characterized by a short file downloads over TCP, with short duration of inactivity or think time in between two file downloads. Under this traffic, Static PSM (SPSM) performs better than CAM, since the STAs in SPSM can switch to low power state (sleep) during think times while in CAM they have to be in the active state all the time. In spite of this gain, performance of SPSM degrades due to congestion, as the number of STAs associated with the access point (AP) increases. To address this problem, we propose an algorithm, which we call opportunistic PSM (OPSM). We show through simulations that OPSM performs better than SPSM under the aforementioned TCP traffic. The performance gain achieved by OPSM over SPSM increases as the mean file size requested by the STAs or the number of STAs associated with the AP increases. We implemented OPSM in NS-2.33, and to compare the performance of OPSM and SPSM, we evaluate the number of file downloads that can be completed with a given battery capacity and the average time taken to download a file.

We present a centralized integrated approach, ADWISER, for (i) managing an Internet access link bandwidth, and (ii) for enhancing the performance of an IEEE 802.11 WLAN. Our single-box approach is an extension to our previous work ([1] & [2]), where we focused on meeting TCP performance objectives over WLANs. In this work, we present a novel cascaded packet scheduling algorithm to address the issue of unfair share of wireless channel between competing high speed LAN-WLAN flows and the Internet-WLAN flows. We demonstrate several ADWISER features which highlight our single-box solution in providing policy based Internet bandwidth management, and giving performance guarantees to both LAN and WLAN users of an enterprise.

A large part of today's multi-core chips is interconnect. Increasing communication complexity has made essential new strategies for interconnects, such as Network on Chip. Power dissipation in interconnects has become a substantial part of the total power dissipation. Techniques to reduce interconnect power have thus become a necessity. In this paper, we present a design methodology that gives values of bus width for interconnect links, frequency of operation for routers, in Network on Chip scenario that satisfy required throughput and dissipate minimal switching power. We develop closed form analytical expressions for the power dissipation, with bus width and frequency as variables and then use Lagrange multiplier method to arrive at the optimal values. We present a 4 port router in 90 nm technology library as case study. The results obtained from analysis are discussed.

We consider the problem of event detection in wireless sensor networks (WSNs) that are large in the sense that an event affects the statistics of the observations of a small number of sensors in the vicinity of where it occurs. An event occurs at a random time at a random location in the region (called the region of interest, ROI) covered by the WSN. We consider a distance based sensing model in which the physical signal sensed by a sensor at a distance d from the event is attenuated by a factor ρ(d). We formulate the problem of detecting an event as early as possible and locating it to a subregion of the ROI under the constraints that the average time to false alarm (TFA) and the average time to false isolation (TFI) are bounded by γ. This formulation is motivated by the change detection/isolation framework introduced by Nikiforov [6]. We extend the decentralized detection procedures MAX [11] and ALL [9], [5], which are designed for colocated networks, to the case of a large WSN where the event localization is also a critical issue. The extended MAX and ALL detect the change and identify a subregion where the event is located. Sensor noise can make the local decisions of ALL toggle rapidly. Motivated by this fact, we propose a distributed change detection/isolation procedure, HALL (Hysteresis modified ALL). We study the supremum average detection delay (SADD) performance of the change detection/isolation procedures MAX, ALL and HALL for a required min{TFA,TFI} ≳ γ. We show that as γ → ∞, the (asymptotic) SADD(ALL) ≤ ln γ ÷ ω 0 M I, SADD(HALL) ≤ ln (γ + 1) ÷ ω 0 (1 − 1/β)M I + C, and SADD(MAX) ≤ ln γ ÷ ω 0 I, where ω 0 , C, β and M are constants that depend on the sensor deployment, the postchange and the prechange distributions of sensor measurements, and I is the Kullback-Leibler divergence between a worst-case postchange distribution and the prechange distribution of sensor measurements. We also compare the SADD of the distributed procedures with that of the asymptotically optimal centralized procedure given by Nikiforov [6] for a Boolean sensing model. We show that the SADD performance of ALL and HALL is of the same order as that of Nikiforov's. We also provide numerical comparison of SADD and TFA for the centralized asymptotically optimal scheme [6], and the distributed schemes MAX, ALL and HALL.

Many basic key distribution schemes specifically tuned to wireless sensor networks have been proposed in the literature. Recently, several researchers have proposed schemes in which they have used group-based deployment models and assumed predeployment knowledge of the expected locations of nodes. They have shown that these schemes achieve better performance than the basic schemes, in terms of connectivity, resilience against node capture and storage requirements. But in many situations expected locations of nodes are not available. In this paper we propose a solution which uses the basic scheme, but does not use group-based deployment model and predeployment knowledge of the locations of nodes, and yet performs better than schemes which make the aforementioned assumptions. In our scheme, groups are formed after deployment of sensor nodes, on the basis of their physical locations, and the nodes sample keys from disjoint key pools. Compromise of a node affects secure links with other nodes that are part of its group only. Because of this reason, our scheme performs better than the basic schemes and the schemes using predeployment knowledge, in terms of connectivity, storage requirement, and security. Moreover, the post-deployment key generation process completes sooner than in schemes like LEAP+., 8 pages, 5 figures, Accepted in ICUMT 2009

We study the performance of greedy scheduling in multihop wireless networks where the objective is aggregate utility maximization. Following standard approaches, we consider the dual of the original optimization problem. Optimal scheduling requires selecting independent sets of maximum aggregate price, but this problem is known to be NP-hard. We propose and evaluate a simple greedy heuristic. We suggest how the greedy heuristic can be implemented in a distributed manner. We evaluate an analytical bound in detail, for the special case of a line graph and also provide a loose bound on the greedy heuristic for the case of an arbitrary graph.

In our earlier work ([1]) we proposed WLAN Manager (or WM) a centralised controller for QoS management of infrastructure WLANs based on the IEEE 802.11 DCF standards. The WM approach is based on queueing and scheduling packets in a device that sits between all traffic flowing between the APs and the wireline LAN, requires no changes to the AP or the STAs, and can be viewed as implementing a "Split-MAC" architecture. The objectives of WM were to manage various TCP performance related issues (such as the throughput "anomaly" when STAs associate with an AP with mixed PHY rates, and upload-download unfairness induced by finite AP buffers), and also to serve as the controller for VoIP admission control and handovers, and for other QoS management measures. In this paper we report our experiences in implementing the proposals in [1]: the insights gained, new control techniques developed, and the effectiveness of the WM approach in managing TCP performance in an infrastructure WLAN. We report results from a hybrid experiment where a physical WM manages actual TCP controlled packet flows between a server and clients, with the WLAN being simulated, and also from a small physical testbed with an actual AP.

We develop analytical models for estimating the energy spent by stations (STAs) in infrastructure WLANs when performing TCP controlled file downloads. We focus on the energy spent in radio communication when the STAs are in the Continuously Active Mode (CAM), or in the static Power Save Mode (PSM). Our approach is to develop accurate models for obtaining the fraction of times the STA radios spend in idling, receiving and transmitting. We discuss two traffic models for each mode of operation: (i) each STA performs one large file download, and (ii) the STAs perform short file transfers. We evaluate the rate of STA energy expenditure with long file downloads, and show that static PSM is worse than just using CAM. For short file downloads we compute the number of file downloads that can be completed with given battery capacity, and show that PSM performs better than CAM for this case. We provide a validation of our analytical models using the NS-2 simulator. In contrast to earlier work on analytical modeling of PSM, our models that capture the details of the interactions between the 802.11 MAC in PSM and certain aspects of TCP.

In this paper, we propose a new security metric for measuring resilience of a symmetric key distribution scheme in wireless sensor network. A polynomial-based and a novel complete connectivity schemes are proposed and an analytical comparison, in terms of security and connectivity, between the schemes is shown. Motivated by the schemes, we derive general expressions for security and connectivity. A number of conclusions are made using these general expressions.

In this paper, we study the Foschini Miljanic algorithm, which was originally proposed in a static channel environment. We investigate the algorithm in a random channel environment, study its convergence properties and apply the Gerschgorin theorem to derive sufficient conditions for the convergence of the algorithm. We apply the Foschini and Miljanic algorithm to cellular networks and derive sufficient conditions for the convergence of the algorithm in distribution and validate the results with simulations. In cellular networks, the conditions which ensure convergence in distribution can be easily verified.

We develop several hardware and software simulation blocks for the TinyOS-2 (TOSSIM-T2) simulator. The choice of simulated hardware platform is the popular MICA2 mote. While the hardware simulation elements comprise of radio and external flash memory, the software blocks include an environment noise model, packet delivery model and an energy estimator block for the complete system. The hardware radio block uses the software environment noise model to sample the noise floor. The packet delivery model is built by establishing the SNR-PRR curve for the MICA2 system. The energy estimator block models energy consumption by Micro Controller Unit(MCU), Radio, LEDs, and external flash memory. Using the manufacturerpsilas data sheets we provide an estimate of the energy consumed by the hardware during transmission, reception and also track several of the MCUs states with the associated energy consumption. To study the effectiveness of this work, we take a case study of a paper presented in [1]. We obtain three sets of results for energy consumption through mathematical analysis, simulation using the blocks built into PowerTossim-T2 and finally laboratory measurements. Since there is a significant match between these result sets, we propose our blocks for T2 community to effectively test their application energy requirements and node life times.

We consider I users sending elastic traffic into a service provider's (SP's) network. Each user has a contract to transmit data at a nominal rate. However, a user is free to transmit at a higher rate if she wishes. For each user, we assume a realistic traffic model. A user alternates between two phases over time. In the limited data phase, a user's transmission rate is capped at some value below her contracted rate. This happens because the user does not have enough data to send. In the unlimited data phase, a user has enough data to sustain any rate. At time ti, a (possibly empty) set Si of users is in the limited data phase. This leaves unutilized resources in the network that ought to be exploited by others. At time t2 > t1, users in Si are back in the unlimited data phase. Now it should be possible for these users to reclaim their contracted rates at the expense of "overusers." We show that under certain conditions, a very simple pricing scheme can ensure fair and efficient operation in the above sense. A SP needs just one price for all the users.

In Universal Mobile Telecommunication Systems (UMTS), the Downlink Shared Channel (DSCH) can be used for providing streaming services. The traffic model for streaming services is different from the commonly used continuously- backlogged model. Each connection specifies a required service rate over an interval of time, k, called the "control horizon". In this paper, our objective is to determine how k DSCH frames should be shared among a set of I connections. We need a scheduler that is efficient and fair and introduce the notion of discrepancy to balance the conflicting requirements of aggregate throughput and fairness. Our motive is to schedule the mobiles in such a way that the schedule minimizes the discrepancy over the k frames. We propose an optimal and computationally efficient algorithm, called STEM+. The proof of the optimality of STEM+, when applied to the UMTS rate sets is the major contribution of this paper. We also show that STEM+ performs better in terms of both fairness and aggregate throughput compared to other scheduling algorithms. Thus, STEM+ achieves both fairness and efficiency and is therefore an appealing algorithm for scheduling streaming connections.

In this paper we are concerned with finding the maximum throughput that a mobile ad hoc network can support. Even when nodes are stationary, the problem of determining the capacity region has long been known to be NP-hard. Mobility introduces an additional dimension of complexity because nodes now also have to decide when they should initiate route discovery. Since route discovery involves communication and computation overhead, it should not be invoked very often. On the other hand, mobility implies that routes are bound to become stale resulting in sub-optimal performance if routes are not updated. We attempt to gain some understanding of these effects by considering a simple one-dimensional network model. The simplicity of our model allows us to use stochastic dynamic programming (SDP) to find the maximum possible network throughput with ideal routing and medium access control (MAC) scheduling. Using the optimal value as a benchmark, we also propose and evaluate the performance of a simple threshold-based heuristic. Unlike the optimal policy which requires considerable state information, the heuristic is very simple to implement and is not overly sensitive to the threshold value used. We find empirical conditions for our heuristic to be near-optimal as well as network scenarios when our simple heuristic does not perform very well. We provide extensive numerical and simulation results for different parameter settings of our model.

The literature on pricing implicitly assumes an "infinite data" model, in which sources can sustain any data rate indefinitely. We assume a more realistic "finite data" model, in which sources occasionally run out of data; this leads to variable user data rates. Further, we assume that users have contracts with the service provider, specifying the rates at which they can inject traffic into the network. Our objective is to study how prices can be set such that a single link can be shared efficiently and fairly among users in a dynamically changing scenario where a subset of users occasionally has little data to send. User preferences are modelled by concave increasing utility functions. Further, we introduce two additional elements: a convex increasing disutility function and a convex increasing multiplicative congestion-penalty function. The disutility function takes the shortfall (contracted rate minus present rate) as its argument, and essentially encourages users to send traffic at their contracted rates, while the congestion-penalty function discourages heavy users from sending excess data when the link is congested. We obtain simple necessary and sufficient conditions on prices for fair and efficient link sharing; moreover, we show that a single price for all users achieves this. We illustrate the ideas using a simple experiment.

In many IEEE 802.11 WLAN deployments, wireless clients have a choice of access points (AP) to connect to. In current systems, clients associate with the access point with the strongest signal to noise ratio. However, such an association mechanism can lead to unequal load sharing, resulting in diminished system performance. In this paper, we first provide a numerical approach based on stochastic dynamic programming to find the optimal client-AP association algorithm for a small topology consisting of two access points. Using the value iteration algorithm, we determine the optimal association rule for the two-AP topology. Next, utilizing the insights obtained from the optimal association rule for the two-AP case, we propose a near-optimal heuristic that we call RAT. We test the efficacy of RAT by considering more realistic arrival patterns and a larger topology. Our results show that RAT performs very well in these scenarios as well. Moreover, RAT lends itself to a fairly simple implementation.

In this paper, we study the performance of client-Access Point (AP) association policies in IEEE 802.11 based WLANs. In many scenarios, clients have a choice of APs with whom they can associate. We are interested in finding association policies which lead to optimal system performance. More specifically, we study the stability of different association policies as a function of the spatial distribution of arriving clients. We find for each policy the range of client arrival rates for which the system is stable. For small networks, we use Lyapunov function methods to formally establish the stability or instability of certain policies in specific scenarios. The RAT heuristic policy introduced in our prior work is shown to have very good stability properties when compared to several other natural policies. We also validate our analytical results by detailed simulation employing the IEEE 802.11 MAC.

The literature on pricing implicitly assumes an "infinite data" model, in which sources can sustain any data rate indefinitely. We assume a more realistic "finite data" model, in which sources occasionally run out of data. Further, we assume that users have contracts with the service provider, specifying the rates at which they can inject traffic into the network. Our objective is to study how prices can be set such that a single link can be shared efficiently and fairly among users in a dynamically changing scenario where a subset of users occasionally has little data to send. We obtain simple necessary and sufficient conditions on prices such that efficient and fair link sharing is possible. We illustrate the ideas using a simple example.

We consider I transport channels on the downlink of an UMTS network, with rate matching attribute (RMA) values RMA/sub 1/, RMA/sub 2/,...RMA/sub I/, that are multiplexed on a single coded composite transport channel (CCTrCh). We derive analytical expressions for the bit error ratios (BERs) seen by each channel in the multiplex. Simulations indicate that the expressions are very accurate. We also provide a procedure that gives the RMA values required to achieve a target set of BERs for a specified signal-to-noise ratio; when no feasible RMA values exist, the procedure indicates that as well. The results of this paper will be of use to UMTS service providers who wish to provide differentiated QoS while maintaining high spectral efficiency.

We consider the problem of on-line routing of bandwidth-guaranteed virtual paths. The basic idea is to route virtual paths such that enough spare capacity is left for accommodating weighted additional demands simultaneously between all other source-destination pairs. The problem formulation results in an integer linear program (ILP), the solution of which gives the optimal routing. However solving the ILP is NP-hard and so we resort to heuristics. We assign weights to the links in the network and then use shortest path routing. The novel aspect of the weight assignment is that the weights take into account the residual link capacities, as well as the number of source-destination pairs that could potentially use the link. Simulations show that the proposed algorithm performs better than existing algorithms in the literature (e.g. MIRA) for a variety of network topologies and traffic scenarios.