We leveraged an unsupervised deep learning (DL) network for blind noise attenuation in a massive multi-input multi-output (MIMO) system without prior knowledge or labeled data. Initially, the real and imaginary parts of the received signal are concatenated in a 2-channel matrix, which is then partitioned into antenna-group patches to improve denoising efficiency. Afterward, our proposed gated recurrent unit (GRU) U-Net (GRUU-Net) network is applied to patch-wise real/imaginary data. The GRUU-Net network consists of gated recurrent units arranged in a U-Net architecture; the encoder extracts salient features from the input, while the decoder reconstructs the input patches. The main idea of GRUU-Net is that it combines the structural denoising capability of U-Net with the sequence modeling strength of GRUs and incorporates attention mechanisms to enhance feature integration within an iterative architecture. The numerical evaluation shows that our proposed model outperforms the benchmark methods across different signal-to-noise ratios (SNRs) and numbers of base station antennas (BSs). Additionally, we confirmed that applying the model simultaneously across multiple subsystems, where each patch can be considered a subsystem serving the same users in the same environment, results in better performance.

Wireless sensor networks (WSNs) consist of power-constrained sensor nodes deployed for various data collection operations in real-world settings. The WSN nodes collect real-time data and send it to a data processing unit (DPU) for in-depth analysis of the collected data with multihop relaying. For sparsely deployed WSNs, data collected from nodes many hops away from the DPU suffer significant delays, thus making such deployments unsuitable for delay-critical applications. However, adding shortcut edges (SEs) directly to the DPU can alleviate the end-to-end transmission delay by incorporating small-world properties. In this paper, we analytically find the optimal locations of a few SEs on a finite-sized linear WSN. Moreover, we also characterize the associated tradeoff in transmit power for using these SEs in the existing linear WSN.

Wireless networks in next generation will provide users ubiquitous computing services with low delay by devices at the network edge, namely mobile edge computing (MEC). The intensive computation tasks can be partially offloaded to the MEC server via the wireless link and then processed through the MEC computation resources to cater for the delay demand. A parallel computation process is formed in the MEC network consists of local computation at MEC users (MUs) and MEC computation at MEC servers. However, the fluctuating wireless channel environment, changeable spatial distribution of MUs and the randomness of MEC servers’ locations make it hard to characterize and guarantee the end-to-end quality of service requirements. In this work, we are devoted to analyze and optimize the overall delay bound for MEC networks under two orthogonal frequency division multiple access (OFDMA) strategies via stochastic network calculus (SNC). Specifically, Poisson cluster process is utilized to capture the randomness of MEC servers’ and users’ spatial locations and to derive the Laplace transform of interference suffered by an MU of interest. The upper bounds for the delay violation probability of two OFDMA strategies are established by exploiting SNC with the Mellin transform of signal-to-interference ratio. Furthermore, we propose an optimal task offloading scheme by minimizing the overall delay, which balances the local computation delay and MEC delay.

The development of the 5G network is envisioned to offer various types of services like virtual reality/augmented reality and autonomous vehicles applications with low-latency requirements in Internet-of-Things (IoT) networks. Mobile-edge computing (MEC) has become a promising solution for enhancing the computation capacity of mobile devices at the edge of the network in a 5G wireless network. Additionally, multiple radio access technologies (multi-RATs) have been verified with the potential in lowering the transmission latency and energy consumption, while improving the Quality of Services (QoS). Benefiting from the cooperation of multi-RATs, large latency-sensitive computing service tasks (L2SC) can be offloaded by different RATs simultaneously, which has great practical significance for data partitioned oriented applications with large task sizes. In this article, to enhance the L2SC offloading services for satisfying low-latency requirements with low energy consumption, we investigate the energy-latency tradeoff problem for partial task offloading in the MEC-enhanced multi-RAT network, considering the limitation of energy and computing in capability-constrained end devices in IoT networks. Specifically, we formulated the L2SC task computation offloading problem to minimize the weighted sum of the latency cost and the energy consumption by jointly optimizing the local computing frequency, task splitting, and transmit power, while guaranteeing the stringent latency requirement and the residual energy constraint. Due to the nonsmoothness and nonconvexity of the formulated problem with high complexity, we convert the tradeoff problem into a smooth biconvex problem and propose an alternate convex search-based algorithm, which can greatly reduce the computational complexity. Numerical simulation results show the effectiveness of the proposed algorithm with various performance parameters.

Attention has been paid to low-cost, light-scattering-based particulate matter (PM) sensors, which provide PM measurements in order to supplement a small number of expensive air quality monitoring stations. However, low-cost PM sensors produce measurement data of questionable quality. In this paper, we evaluate the performance of low-cost PM sensors, specifically PurpleAir PA-II units. To evaluate the PurpleAir PA-II units, we use accurate air quality data measured from monitoring stations within close proximity to the PA-II units as reference. By means of linear regression, we compare PurpleAir PA-II units with air quality monitors. From the result, PurpleAir PA-II units have high correlations (R2≥ 0.84) with nephelometers, which are based on the principle of light-scattering, and thus the PurpleAir PA-II is a sufficient substitute for nephelometers. PurpleAir PA-II units have a good agreement (R2= 0.72 and 0.89) with MetOne BAM 1020 monitors based on beta ray attenuation but show a non-linear behavior. Furthermore, there is an essential observation that the PurpleAir PA-II unit needs to have significantly high precision in order to have a high correlation with an expensive reference monitor and thus be used supplementally. The considered PurpleAir PA-II units overestimate PM2.5concentrations compared with air quality reference monitors. Therefore, a calibration algorithm for PurpleAir PA-II units should be considered to give a correct air quality index at sites considered in this paper. However, our results show the PurpleAir PA-II to be a promising low-cost air quality sensor for supplementing a conventional air quality sensing network with expensive monitors.

Time- and jitter-sensitive traffic, such as VoIP and live streaming, have made fast Wi-Fi roaming an important topic in mobile communications. Conventional Wi-Fi roaming is generally initiated by clients, which have limited understanding of the network topology and the surrounding environments. In this paper, we couple localization and roaming together. We present an on-demand localization technique at the infrastructure side that uses a standard 802.11v protocol to collect information necessary for localization. The location information is then used in a roaming decision. Our approach does not require any client-side modification because we exploited the capabilities of Wi-Fi standards and the existing control logic in most current Linux/Android-based systems. To demonstrate the effectiveness of our approach, we provide experimental evidence of implementation in an enterprise-level wireless network.

The future 5G wireless network is largely driven by the increasing heavy traffic and spectrum scarcity. Cognitive Radio (CR) techniques provide a potential solution for improving the spectrum efficiency. In this paper, we study the stochastic framework for the CR networks, considering different quality of service (QoS) requirements. To analyze the performance of the CR network, we adopt a poisson point process (PPP) to capture the mobility and randomness of user location. A stochastic-network-calculus (SNC) based approach is proposed to model the wireless transmission and evaluate the network performance. In order to achieve the performance metrics of end-to-end (E2E) delay and backlog in the entire network, we propose a new conception named as effective service process (ESP) which is able to capture the QoS requirements of users. Furthermore, we evaluate the performance in the exponential domain, which can present the E2E analysis more directly. The simulation results verify the theoretical analysis and show that the performance in the CR networks can be derived perfectly with the proposed approach, considering the stochastic traffic arrival and designed service model in our schedule.

Energy harvesting with combination of multiple cooperating radio access technologies (multi-RAT) is regarded as a promising network paradigm to improve the energy efficiency of 5G networks. In this paper, we propose a resource-on-demand energy scheduling strategy for multi-RAT wireless networks, where the varying energy demand of the network can be satisfied by both grid power and harvested energy. Due to the high sensitivity to uncertainties of energy harvesting, a dynamic network energy queue model is designed first considering the inherently stochastic and intermittent nature of the harvested energy. Then, to minimize time-averaged grid power consumption and make effective utilization of harvested energy, the energy scheduling is formulated as a stochastic optimization problem subject to data queue stability and harvested energy availability, considering the high dynamics of wireless channel states and renewable energy sources. Following the Lyapunov optimization framework, the stochastic grid power minimization problem is decomposed into a network flow control subproblem, a network energy management subproblem, and a network resource allocation subproblem, respectively. In order to solve these subproblems, we develop a dynamic adaptive resource-on-demand (DAROD) algorithm to effectively reduce the grid power consumption cost by allocating the resource efficiently based on the dynamic demands of multi-RAT networks. Finally, the tradeoff between grid power consumption cost and network delay is achieved, in which the increase of network delay is approximately linear with the network control parameter V and the decrease of grid power consumption cost is at the speed of 1/V. Extensive simulations are conducted to verify the theoretical analysis and show the effectiveness of our proposed algorithm.

To satisfy the high requirements on operation efficiency in the 5G network, self-organizing network (SON) is envisioned to reduce the network operating complexity and costs by providing SON functions, which can optimize the network autonomously. However, different SON functions have different time scales and inconsistent objectives, which leads to conflicting operations and network performance degradation, raising the needs for SON coordination solutions. In this paper, we devise a multiple time-scale coordination management scheme (MTCS) for densely deployed SONs, considering the specific time scales of different SON functions. Specifically, we propose a novel analytical model named M time-scale Markov decision process, where SON decisions made in each time-scale consider the impacts of SON decisions in other M - 1 time scales on the network. Furthermore, in order to manage the network more autonomously and efficiently, a Q-learning algorithm for SON functions in the proposed MTCS scheme is proposed to achieve a stable control policy by learning from history experience. To improve energy efficiency, we then evaluate the proposed MTCS scheme with two functions of mobility load balancing and energy saving management with designed network utility. The simulation results show that the proposed SON coordination scheme significantly improves the network utility with different quality of experience requirements while guaranteeing stable operations in wireless networks.

In this paper, we consider an electric vehicle (EV) charging schedule together with appliance scheduling in a residence under a day-ahead real-time pricing scheme (DA-RTP). Among demand response (DR) programs, EVs are an important resource for reducing energy cost due to high flexibility in energy scheduling. On the other hand, the required amount of energy to charge an EV has a counter effect on cost reduction. In a scheduling problem, a constraint on state-of-charge (SoC) of an EV when departing could be a factor in increased cost. Thus, instead of the constraint, we introduce a dissatisfaction at SoC when departing in the objective of the scheduling problem. We formulate our scheduling problem for minimizing a consumer's total dissatisfaction as a mixed-integer nonlinear programming (MINLP) problem since we consider shiftable but uninterruptible loads, which need an On/Off decision. We adopt an outer approximation algorithm to efficiently obtain an optimal solution.

Recently, millimetre‐wave (mmWave) wireless fronthauls have been regarded as an effective solution to deploy remote radio heads with higher flexibility and efficiency in cloud radio access networks (C‐RANs). Different from the traditional fibre fronthauls, in order to maximise the utilisation of the time‐frequency resource, the mmWave wireless fronthauls are more expected to operate in a dynamic allocation manner. In this study, the energy efficient mmWave fronthaul and OFDMA resource optimisation in C‐RANs is investigated. The TDMA‐based fronthaul allocation mechanism is first presented and then the joint resource optimisation is formulated as an energy efficiency (EE) maximisation problem which is in the form of a mixed‐integer non‐linear fractional programming (MINLFP) problem. By taking advantage of the Dinkelbach method, the MINLFP problem is transformed into a subtractive optimisation problem and solved by using the Lagrange dual decomposition theory. Moreover, a maximal weighted bipartite graph matching approach is proposed to determine the optimal resource block allocation. Finally, extensive simulation results are provided to evaluate the EE performance of the proposed algorithm by comparing with several benchmark schemes, and it shows that the proposed algorithm can achieve great EE performance gain over the benchmark schemes.

A promising approach for dealing with the increasing demand of data traffic is the use of device-to-device (D2D) technologies, in particular when the destination can be reached directly, or though few retransmissions by peer devices. Thus, the cellular network can offload local traffic that is transmitted by an ad hoc network, e.g., a mobile ad hoc network (MANET), or a vehicular ad hoc network (VANET). The cellular base station can help coordinate all the devices in the ad hoc network by reusing the software tools developed for software-defined networks (SDNs), which divide the control and the data messages, transmitted in two separate interfaces. In this paper, we present a practical implementation of an SDN MANET, describe in detail the software components that we adopted, and provide a repository for all the new components that we developed. This work can be a starting point for the wireless networking community to design new testbeds with SDN capabilities that can have the advantages of D2D data transmissions and the flexibility of a centralized network management. In order to prove the feasibility of such a network, we also showcase the performance of the proposed network implemented in real devices, as compared to a distributed ad hoc network.

The increasing number of connected vehicles in densely populated urban areas provides an interesting opportunity to counteract the high wireless data demands in high density and highly mobile scenarios. The idea is to support the macro base station (BS) with a secondary communication tier composed of a set of smart and connected vehicles that are in movement in the urban area. As a first step towards a comprehensive cost-benefit analysis of this architecture, this paper considers the case where these vehicles are equipped with femto-mobile Access Points (fmAPs) and constitute a mobile out-of-band relay infrastructure. In particular, three techniques to select an fmAP (if more than one is available) are proposed and the maximal feasible gain in the data rate is characterized as a function of the vehicle density, average vehicle speeds, handoff overhead cost, as well as physical layer parameters. The analytical and simulation results provide a first benchmark characterizing this architecture and the definition of guidelines for its future realistic study and implementation.

The heart rate variability (HRV) is the variation in the pulsing frequency of the human heart. Measuring this parameter can reveal important information on the real-time interaction between the autonomic nervous system and the cardiocirculatory system. It can provide useful insight on an individual's state of stress or well being even outside a clinical setting, thanks to inexpensive and unobtrusive wireless sensors and the computing capability of our smartphones. These sensors are battery operated, so their current sampling frequency may be inadequate to measure HRV parameters. In this article, we focus on the accuracy of the detection of the RR interval time series (the instantaneous heart rate), and we investigate the sampling frequency needed to obtain a given level of accuracy for different signals and HRV parameters. We provide the guidelines for an opportunistic choice of the sampling rate to achieve a desired accuracy, and we propose a series of techniques to improve this accuracy with a fixed sampling frequency. We show the effectiveness of the proposed techniques in terms of relative error reduction and energy savings for the wireless sensors.

We propose a traffic safety metric called the safety marginal value (SMV) to be applied to discrete-time and continuous-space vehicular traffic networks. Every vehicle uses a set of vehicle states containing the position, velocity, and lane index of all vehicles on a roadway to determine the SMV, while also controlling its velocity for the next time step. The anterior SMV is defined as the minimum value from a set of the continuous levels of collision risk with the leading vehicles predicted by the collision avoidance (CA) margin time of the designated vehicle and is bounded by two non-negative integers. The higher the anterior SMV, the lower the likelihood of a rear-end accident occurring. This simple and rigorous traffic safety metric will be useful in reducing vehicle-to-vehicle crashes and could thus relieve traffic congestion caused by accidents. Moreover, the anterior SMV can be used as a safety criterion to validate car- following models under various environmental variables or as a key parameter of an objective function to maximize safety levels on roadways.

In this paper, we investigate the resource allocation for orthogonal frequency division multiple access relay networks, where the relay does not have embedded energy supply and needs to first harvest energy from the received signals from the source before forwarding transmission. The relay uses time switching scheme for wireless information and power transfer. We aim to maximize the weighted sum rate under several constraints by varying the source transmission power, the relay transmission power, and the time switching ratio. We formulate the joint resource allocation problem as an optimization problem, which is non-convex. Although it is difficult to solve the non-convex problem, we derive its closed-form solution by exploiting its special structure. We also prove that the closed- form solution is a partial optimum. Finally, simulations verify the proposed closed-form solution is superior to the equal power solution.

For the TV white space (TVWS) in a wireless regional area network (WRAN), wireless microphone (WM) signals must be detected as primary users. Since the very narrow band of a WM signal, there will be several spectrum fragments after spectrum sensing. In our work, a singular value decomposition (SVD) based approach is presented to detect multiple WM signals and then to select component carriers (CCs) and further implement carrier aggregation (CA) in a wideband Cognitive Radio (CR) network. Simulation results prove the better detection performance over the traditional energy detection, and the proposed CC selection approach works effectively compared to the blindly CC assigning method.

There have been many studies for modeling vehicular traffic flow using fluid models. However, these previous approaches do not accommodate realistic models for traffic density, flow, and velocity. The existing models also fail to uncover the relationships among energy efficiency, capacity, and safety. We investigate traffic networks from a system-level perspective. In result, we provide a time-gap based mathematical traffic model for vehicular traffic flow on highways. Our model explains the widely known triangular fundamental diagram, which represents vehicular traffic systems with the three primary parameters: maximum free-flow velocity, a typical safety length of vehicles, and a mean value of the time-gap of the traffic data during congested conditions. This result is also well validated with measured traffic data using least squares matching and with previous research outcomes about the propagation velocity. In addition, we suggest two distinct analysis techniques to estimate the time-gap from the traffic data measured on highways.

Numerous studies have examined ramp-metering control to relieve highway congestion. Unlike previous research, this paper presents two different optimization problems for maximum system capacity over a highway corridor, using both a time-gap based traffic model describing traffic flow and the limited traffic data measured by existing field facilities. Our proposed algorithms are coordinated ramp-metering controls controlling the metered rates at system-wide entrance ramps. The origin- utilization relationship is taken into consideration in providing the mathematical derivation for the steady-state optimization problem. This scheme regulates on-ramp flows so as to keep traffic densities along the system below their critical densities. To prevent an increase in adjacent street traffic, which might be caused by this scheme, a time-variant linear programming problem is provided with on-ramp queue control and traffic flow estimation. Comparative simulation results for two optimization problems are presented.

Cognitive networking paradigms may help meet the challenges of operating complex wireless communications networks. In this paper, we contrast the neural network (NN) and the Bayesian network (BN) models to extract information from real-time observations and optimize network performance. In particular, we apply these two models to the problem of call admission control (CAC) for a long term evolution (LTE) system. We simulate a realistic LTE scenario with mobility in ns-3 and we select the most relevant features that can be observed by the base station. Then, we design two new CAC schemes that autonomously learn the network behavior from the observation of the selected features. Furthermore, we propose a performance comparison among these two schemes and a state-of-the-art CAC scheme, showing that the NN and the BN schemes are very promising solutions for CAC in LTE systems.

"The search for biomarkers of stress and health remains a challenging task for researchers and clinicians alike," as noted in [9]. Against this backdrop, the recent emergence of medical devices that can collect time series for long durations at very high sampling rates makes it possible to study temporal patterns in biophysical signals. We demonstrate a functional system to collect and analyze physiological signals, and provide real-time feedback to the end user.

The human heart rate is influenced by different internal systems of the body and can reveal valuable information about health and disease conditions. In this paper, we analyze the instantaneous heart rate signal using a Bayesian method, inferring in real time a probabilistic distribution that approximates the real distribution of this signal. The best model is chosen after an experimental analysis of real data collected within our framework. The parameters of this distribution can reveal interesting insights on the influences of the sympathetic and parasympathetic divisions of the autonomic nervous system (ANS) in real time.

The study of group dynamics is of primary importance in psychology and medicine because group dynamics affects the state of each member in a group. We study the RR interval time series, a heart rate measure, for a group of individuals involved in Kundalini meditation sessions. We analyze individual signals and study the wavelet coherence among the heart rate variability of different individuals. For specific activities, we found a high degree of coherence among all the people in the group. We also propose a novel method to detect temporally varying connections among the individuals based on the coherence of their heart rate.

The use of wireless technology and advanced signal processing for personalized healthcare is extremely promising. A relevant application appears to be the field of group dynamics, in which the study of a heart-rate measure, the RR interval time series, can reveal valuable information about individuals, as well as the group as a whole. In this paper, we present the results of computing the wavelet coherence among the RR interval time series of a group of people during a Kundalini yoga meditation session, revealing entrainment among them during specific activities and additional important information, such as patterns of heart rate variability that are common to all members of the group. We propose a novel method to study the connections among people in real time, underlying the bounds in the accuracy as a function of the delay introduced.

This paper describes the design, deployment, and empirical evaluation of WIISARD - a novel emergency response system that provides reliable communication in dynamic wireless environments without extensive communication infrastructure. The main contribution of this paper is an in-depth empirical study of network properties that emerge during a drill in which WIISARD is deployed with minimal infrastructure support. The drill involves 19 first responders and 41 victims. The properties of links established among first responders vary between phases of the drill and depend upon the responder's role in the drill. The rescue phase - in which responders are highly mobile as they triage victims - poses significant challenges to reliable communication. During this phase, the contacts between responders are short-lived; however, they are reestablished within minutes. Once a contact between responders is established, the quality of the link between those responders is usually high. The connectivity graph observed during the rescue phase is usually connected and has a small diameter although there are times when it has a large diameter or it is partitioned. While mobility increases network dynamics, we also observe that the mobility patterns characteristic of the emergency response workflow can be leveraged to disseminate data efficiently through data muling. WIISARD employs a gossip-based protocol and supports data dissemination through local communication and data muling to achieve 98% reliability during the drill exercise. These results indicate the feasibility of providing reliable communication in emergency response with minimal infrastructure in spite of network dynamics.

BACKGROUND: There is growing interest in the use of technology to enhance the tracking and quality of clinical information available for patients in disaster settings. This paper describes the design and evaluation of the Wireless Internet Information System for Medical Response in Disasters (WIISARD). MATERIALS AND METHODS: WIISARD combined advanced networking technology with electronic triage tags that reported victims' position and recorded medical information, with wireless pulse-oximeters that monitored patient vital signs, and a wireless electronic medical record (EMR) for disaster care. The EMR system included WiFi handheld devices with barcode scanners (used by front-line responders) and computer tablets with role-tailored software (used by managers of the triage, treatment, transport and medical communications teams). An additional software system provided situational awareness for the incident commander. The WIISARD system was evaluated in a large-scale simulation exercise designed for training first responders. A randomized trial was overlaid on this exercise with 100 simulated victims, 50 in a control pathway (paper-based), and 50 in completely electronic WIISARD pathway. All patients in the electronic pathway were cared for within the WIISARD system without paper-based workarounds. RESULTS: WIISARD reduced the rate of the missing and/or duplicated patient identifiers (0% vs 47%, p<0.001). The total time of the field was nearly identical (38:20 vs 38:23, IQR 26:53-1:05:32 vs 18:55-57:22). CONCLUSION: Overall, the results of WIISARD show that wireless EMR systems for care of the victims of disasters would be complex to develop but potentially feasible to build and deploy, and likely to improve the quality of information available for the delivery of care during disasters.

In this paper, we investigate the machine learning based strategies for dynamic channel selection in Cognitive Access Points (CogAPs) of WLANs. We employ Multi-layer Feedforward Neural Network (MFNN) models that utilize historical traffic information from network environment for learning the influence of spatio-temporal-spectral factors on the network and then predicting future traffic loads on each of the channels. Based on the future traffic loads, CogAP chooses the best channel for serving wireless clients. An important factor is the time scale of traffic prediction. We construct three kinds of traffic predictors that predict traffic at different time scales: MLP (Minute Level Prediction), MILP (Minute Interval Level Prediction), and HLP (Hourly Level Prediction) schemes and study their prediction accuracy. Experiment results show that MFNN predictors perform better than traditional autoregressive models in terms of prediction accuracy. In addition to accurate prediction, another factor that influences the design of cognitive network channel selection is the impact of channel selection strategy on the transport layer performance. We, therefore, conduct performance studies on the TCP throughput achieved on the above mentioned cognitive channel selection strategies. The MFNN predictors will also help CogAP to find and switch to the optimal channel, leading to a higher and more sustained throughput.

Cognitive networking deals with applying cognition to the entire network protocol stack for achieving stack-wide as well as network-wide performance goals, unlike cognitive radios that apply cognition only at the physical layer. Designing a cognitive network is challenging since learning the relationship between network protocol parameters in an automated fashion is very complex. We propose to use Bayesian Network (BN) models for creating a representation of the dependence relationships among network protocol parameters. BN is a unique tool for modeling the network protocol stack as it not only learns the probabilistic dependence of network protocol parameters but also provides an opportunity to tune some of the cognitive network parameters to achieve desired performance. To the best of our knowledge, this is the first work to explore the use of BNs for cognitive networks. Creating a BN model for network parameters involves the following steps: sampling the network protocol parameters (Observe), learning the structure of the BN and its parameters from the data (Learn), using a Bayesian Network inference engine (Plan and Decide) to make decisions, and finally effecting the decisions (Act). We have proved the feasibility of achieving a BN-based cognitive network system using the ns-3 simulation platform. From the early results obtained from our cognitive network approach, we provide interesting insights on predicting the network behavior, including the performance of the TCP throughput inference engine based on other observed parameters.

In this paper, we present an application of the Cognitive Networking paradigm to the problem of development of autonomous Cognitive Access Point (CogAP) for small scale wireless network environments such as Wi-Fi hotspots and home networks. In these environments we typically use only one AP per service provider/residence for providing wireless services to the users. However, note that larger number of APs from multiple service providers/residences vie for bandwidth in any geographic region. Here we can reduce the cost of autonomic network control by equipping the same AP with a cognitive functionality. We first present architecture of our autonomous CogAP. Then we introduce our algorithmic solution, in which a Neural Network-based traffic predictor makes use of historical traffic traces to learn network traffic conditions and predicts traffic loads on each of 802.11 b/g channels. The cognitive decision engine makes use of traffic forecasts to dynamically decide which channel is best for CogAP to operate on for serving its clients. One of the challenges in autonomous cognitive decision making is the computation resource constraints in today's embedded APs. We have built a prototype CogAP device using cognitive software modules and off-the-self hardware components. We carried out performance evaluation of the proposed CogAP system by conducting experimental measurements on our testbed platform; the obtained results show that the proposed CogAP is effective in achieving performance enhancements with respect to state-of-the-art channel selection strategies.

In this paper, we present an application of the cognitive networking paradigm to the problem of dynamic channel selection in infrastructured wireless networks. We first discuss some of the key challenges associated with the cognitive control of wireless networks. Then we introduce our solution, in which a Neural Network-based cognitive engine learns how environmental measurements and the status of the network affect the performance experienced on different channels, and can therefore dynamically select the channel which is expected to yield the best performance for the mobile users. We carry out performance evaluation of the proposed system by experimental measurements on a testbed implementation; the obtained results show that the proposed cognitive engine is effective in achieving performance enhancements with respect to state-of-the-art channel selection strategies.

Traffic sensing and characterization is an important building block of cognitive networking systems; however, it is very challenging in multi-channel multi-radio wireless networks. The contributions of this paper include the following: (i) a discussion of packet sampling for traffic sensing in multi-channel wireless networks, (ii) a comparison of various time-based sampling strategies using the Kullback-Leibler Divergence (KLD) measure, (iii) a study of the effect of the sampling parameters on the accuracy of the sampling strategies, (iv) the proposal of a new metric (Traffic Intensity) which estimates the busyness of channels by taking into consideration not only the successfully received packets but also corrupt or broken packets, and (v) some preliminary results on the characterization of a campus 802.11 network environment in a spatio-temporal fashion.

In this paper, we address the problem of computing the probability that r out of n interfering signals can be correctly received in a random access wireless system with capture. We extend previous results on the capture probability computation, and provide an expression for the distribution of the number of captured packets that is scalable with n and r. We also provide an approximate expression, that is much easier to compute and provides good results for r = 0 and r = n. Finally, we study the dependence of the system throughput performance on the multi-packet reception capabilities of the receiver.

In this paper, we propose packet size aware path setup mechanisms for 802.11 based multi-hop WLAN networks. Path setup optimization is achieved by minimizing the transmission delay experienced by each packet traversing from source to the destination where different packets belonging to the same source destination pair can traverse different paths based on their sizes. We implemented a sample packet size aware path setup scheme as a Linux kernel module and experimentally showed the benefits of such a scheme in terms of the transmission delay and the throughput in an 802.11b WLAN environment. In addition to that we examine general path setup solutions for wireless networks considering packet size statistics.

In this paper, we argue that network performance can be improved when nodes explicitly exchange protocol information with each other. We present a vision of network society for next generation wireless networks that entails such social networking. We begin by describing our cognitive social network (CosNet) system architecture that enables network nodes to effectively gather, analyze, compact, repositorize, and exchange network experience information. We also describe a host of technical issues that need to be addressed for successful realization of a network society, including the management of control overhead, protecting user privacy, vulnerability to selfish and malicious attacks, and scalability concerns. We demonstrate the utility of our approach by studying CosNet inspired modifications of the IEEE 802.11 MAC algorithm that we call CosMAC, respectively. Simulation results show that CosMAC outperforms the throughput of 802.11 MAC in single-hop wireless LAN scenarios. CosMAC also appears to result in a fairer allocation, recorded by 10-15% improvement in Jain's fairness index.

In this paper, throughput performance of WMNs is studied. In our model, a regular grid backbone network overlays on a random ad hoc network. We propose a framework to calculate non-asymptotic throughput, which can be obtained by computing several deterministic parameters. Two problems are investigated. In Maximum Throughput Partition (MTP) problem, the ideal throughput is achieved by optimally partitioning the network with a proper number of backbone nodes. In Maximum Throughput Partition with Hops' number Constraint (MTPHC) problem, a similar problem is studied but with constraint on the average number of hops in the backbone network. The results show that it is critical to find an appropriate size of the backbone network for a WMN, especially when the hops' number constraint is imposed Our solution of MTPHC problem can be also used to obtain the ideal transmission range when less-than-optimal number of backbone nodes is deployed. Comparing with the minimum transmission range, the ideal one can achieve the same optimal throughput but effectively reduce the average number of hops in mesh backbone communications.

In this paper, we propose a novel asynchronous media access control (MAC) protocol, opportunistic MAC (OMAC), for multiple input multiple output (MIMO) ad-hoc networks. The proposed solution is based on closed loop minimal feedback antenna selection diversity scheme and optimum receive combining. The use of antenna selection diversity contributes to a reduction in the feedback information and the effective interference produced. To utilize the spatial degrees of freedom offered by MIMO, we propose the use of a novel rank based metric to obtain interference information as well as to enable multiple simultaneous transmissions and to make MAC decisions. The rank of the interference matrix, (RI) is used as a metric. We present the performance of the proposed solution from the throughput perspective for a single hop ad-hoc wireless network. Through analysis and simulation, we found that the proposed protocol significantly outperforms 802.11 MIMO and it obtained as high spatial degree of freedom utilization as 85%.

In an ultra-wide band (UWB) sensor network signal reflections from objects can be used to accurately determine the location. UWB signals are preferred in these types of sensor networks since they provide a very good resolution due to their fine time granularity. We propose an artificial neural network based localization algorithm to detect single object in a sensor network and compare its performance to Cramer-Rao bound and least squares estimator. Then we propose a two phase algorithm for multiple object detection and evaluate the algorithm for the case when there are two objects in a sensor network with three nodes.

Localization is becoming more important with increasing number of cellular phone users. Due to safety aspects with increased emergency calls from mobile phones, new applications related to location based services, and the network optimization with increasing load, localization draws interest from both the academia and the industry. In this study, we propose a neural network based algorithm that uses multipath strengths to locate a mobile user without a GPS receiver. We validated our algorithm in a commercial network.

Many wireless network standards include quality-of-service (QoS) features at the MAC layer. These features provide nodes transmitting high priority delay sensitive traffic such as voice and video preferential access to the channel over nodes carrying low priority delay tolerant traffic such as file transfer and email. However, such schemes are unfair to low priority users, depriving them of equitable transmission opportunities, and causing throughput starvation for their applications. Such unfairness can provoke rational nodes carrying low priority traffic to falsely declare their traffic as high priority in order to maximize their throughput, thereby defeating the very purpose of QoS differentiation. In this paper, we provide game-theoretic analysis of a slotted Aloha like MAC that resembles the IEEE 802.11e MAC in many essential respects. Our MAC model allows traffic to be classified as either high-priority (HP) or low-priority (LP), and allows for both random access (contention) and polled (contention-free) channel access. We advocate an incentive mechanism to stimulate LP users to be truthful. This incentive mechanism makes use of the contention-free channel access feature of our MAC as an efficient and protocol-compliant mechanism to encourage low priority users to be truthful. We discuss appropriate utility functions for HP and LP traffic and use a fixed point analysis to derive the performance of the system in terms of the fraction of time the system is operated in contention-free mode. We find the condition for which our incentive mechanism results in a truthful Nash equilibrium, i.e., no user has an incentive to unilaterally lie about her traffic type. We then use the Nash bargaining solution (NBS) concept to suggest how an AP can pick an operating point using our incentive mechanism to ensure fairness and Pareto- optimality.

Wireless network characterization is an important task in next generation wireless networks. In order to achieve efficient wireless network characterization, accurate sampling strategies are required. The relative performance of different sampling strategies for assessing various wireless network traffic metrics is significant due to the complexity and expense involved in the collection, storage, and analysis of all the traffic generated in the wireless medium. Since the spectrum used for most wireless networks, especially those based on IEEE 802.11 standards, is divided into several channels, the existing count-based sampling methods demand continuous capture on each channel for selecting the desired packets of interest. Continuous capturing makes the cost of monitoring infrastructure very expensive and hence count-based sampling methods are not scalable. However, the time-based sampling methods which were considered inaccurate in wired network characterization, appear to offer a cost-effective and scalable solution by reducing the cost of resources necessary to accurately characterize the wireless medium. For example, the use of time-based sampling enable us to make use of a single wireless interface for accurately sampling multiple channels. However, in order to achieve this, we need to identify the right set of parameters for time-based sampling. This paper presents a study of the performance of various time-based sampling methods in answering questions related to their use in wireless network traffic characterization. We simulate time-based sampling traces at a variety of granularities using a complete packet trace (i.e., parent population) captured in a campus wireless network environment that aggregates traffic from a large number of nodes. From our analysis using Chi-square test, we found that the timer-driven time-based sampling is more accurate than count-driven time-based sampling for both systematic and stratified sampling schemes.

During an emergency response, access to a reliable communication infrastructure is required to exchange accurate information in a timely manner. Various communication technologies have been deployed for emergency response; however communication between different first response organizations has always been a problem. This is due to either broken networks or lack of knowledge regarding the channel frequency in use for the same device. According to recent investigations, text messaging was shown to be more reliable than voice to exchange short messages carrying critical information. Additionally, posting and updating the information on an electronic webpage accessible to all is also very useful. In addition, we would also suggest that team leaders physically stand together, thus improving network resource utilization plus ensuring receipt of updates and information from peers in the event the higher ranked person in the hierarchy is not reachable. In this paper, we present supporting arguments for the choice of a wireless mesh network as a candidate to provide communication infrastructure for emergency response. We also present a comprehensive set of technical, social and organizational challenges which we experienced first hand during several deployments, learned about in interviews with emergency responders and by examination of the after-incident reports. Many of these challenges become even more of a concern and have a greater impact on international disasters concerning multiple countries when traditionally different technologies are used often in conjunction with different languages. We also present the results of network performance analysis which identifies sources of bottleneck and overhead in communication. A distributed control hierarchical authority is necessary to prevent bottleneck and the need to cancel an already scheduled path due to resource unavailability or security breach.

An infrastructure wireless mesh network (WMN) is a hierarchical network consisting of mesh clients, mesh routers and gateways. Mesh routers constitute a wireless mesh backbone, to which mesh clients are connected as a star topology, and gateways are chosen among mesh routers providing Internet access. In this paper, the throughput capacity of infrastructure WMNs is studied. For such a network with Nc randomly distributed mesh clients, Nr regularly placed mesh routers and Ng gateways, assuming that each mesh router can transmit at W bits/s, the per-client throughput capacity has been derived as a function of Nc , Nr , Ng and W . The result illustrates that, in order to achieve high capacity performance, the number of mesh routers and the number of gateways must be properly chosen. It also reveals that an infrastructure WMN can achieve the same asymptotic throughput capacity as that of a hybrid ad hoc network by choosing only a small number of mesh routers as gateways. This property makes WMNs a very promising solution for future wireless networking.

Cognitive radio networking research today mainly focuses on finding efficient ways to let secondary users access radio spectrum that is licensed to primary users, with minimal interference to the license owners. Physical layer cognition, though very important, is complex, expensive, and can provide only limited information about the higher layer traffic. We argue that, even in the absence of physical layer cognitive capability, higher layer traffic information can still be used to generate sufficient cognitive networking information to improve system performance. In this paper, we present an architecture for cognitive networking and an early prototype and experimental setup of a cognitive network access point (CogNet AP), and we describe our observations and lessons learned from this experimental activity. The CogNet AP gathers, processes, analyzes, and stores information available through its monitoring interface in order to build a cognitive local repository which holds the spatio-temporally tagged network traffic information. The inexpensiveness of the components used for building the CogNet AP shows the flexibility of building Cognitive Network elements compared to cognitive radio devices. The proposed cognitive networking architecture and prototype point to the many possible application scenarios and research potential for such systems which use temporal patterns of higher layer traffic information. From our experiments we found that the use of cognitive information derived from higher networking layers resulted in achieving better system throughput.

Though the popular IEEE 802.11 DCF is designed primarily for wireless LAN (WLAN) environments, today it is being widely used for wide area wireless mesh networking. The protocol parameters of IEEE 802.11 such as timeout values, interframe spaces, and slot durations, which are sufficient for a general WLAN environment need to be modified in order to efficiently operate in wide area wireless mesh networks. The current wide area wireless mesh network deployments use manual configuration of these parameters to the upper limit which essentially makes the networks operate at lower system efficiency. In this paper, we propose d802.11 (dynamic 802.11) which dynamically adapts the protocol parameters in order to operate at varying link distances. We present three strategies, (i) multiplicative timer back-off (MTB), (ii) additive timer back-off (ATB), and (iii) link RTT memorization (LRM), to adapt theACK_TIMEOUTin d802.11 in order to provide better adaptation for varying link dimensions. Through extensive simulation experiments we observed significant performance improvement for the proposed strategies. We also theoretically modeled the maximum throughput as a function of the link dimension for the proposed system. Our results show that the LRM technique provides the best adaptation compared to all other schemes.

Many wireless network standards include quality-of-service (QoS) features at the MAC layer. These features provide nodes transmitting real-time traffic such as voice and video preferential access to the channel over nodes carrying best-effort traffic. The success of these QoS mechanisms requires that nodes be honest and truthfully report their application's QoS category. However rational nodes will, if they can, deviate from a standard's specification to maximize their utility. Network interfaces are becoming increasingly programmable and it is possible for nodes to falsely classify their best-effort traffic as real-time traffic to obtain increased throughput. In this paper, we provide a game-theoretic analysis for a slotted Aloha like MAC that resembles the IEEE 802.11e MAC in many essential respects. Our MAC model allows traffic to be classified as either high-priority (HP) or low-priority (LP), and allows for both random access (contention) and polled (contention-free) channel access. We advocate the use of the contention-free access feature as an efficient and protocol-compliant mechanism to incentivize LP users to be truthful. We discuss appropriate utility functions for HP and LP traffic and analyze the performance of the system using the Nash bargaining solution (NBS) concept from cooperative game theory. The NBS concept is used to find a fair and Pareto-optimal operating point for our system. Since users are strategic, we then use the framework of non-cooperative game theory to find the set of Nash equilibria. Somewhat remarkably, we find that the NBS operating point is a Nash equilibrium, implying that our strategy is both efficient and strategy-proof.

emergency communication infrastructure should allow fast and reliable information dissemination to assist community and ease mitigation activities. Failure in communication networks and information exchange in past has impeded the responders' efforts resulting in huge loss of lives and economical impacts. Reliability, quick reconfiguration and interoperability are specific requirements of a robust communication infrastructure at disaster sites. We have deployed a wireless mesh test bed at several drills on campus and in the city to identify the vulnerabilities of the existing communication infrastructure and enhance the network capacity and performance. We present the real measurements obtained over the deployment of the wireless mesh test bed at disaster site followed by an analytical discussion of the important observations concerning the factors that impact performance or cause network congestion.

We are concerned with maximizing the lifetime of a data-gathering wireless sensor network consisting of set of nodes directly communicating with a base-station. We model this scenario as the m-message interactive communication between multiple correlated informants (sensor nodes) and a recipient (base-station). With this framework, we show that m-message interactive communication can indeed enhance network lifetime. Both worst-case and average-case performances are considered.

Establishing and accessing a reliable communication infrastructure at crisis site is a challenging research problem. Failure in communication infrastructure and information exchange impedes the early response efforts resulting in huge loss of lives and economical impacts. Reliability, robustness, interoperability and minimum interdependencies are specific requirements of communication technology within the context of emergency applications. We present the real measurements obtained over the deployment of a quickly configurable and easily reconfigurable wireless mesh test bed at disaster site. This is followed by an analytical discussion of the important observations concerning the factors that impact performance or cause bottlenecks.

Communication infrastructure has some specific requirements that need to be considered within the context of emergency response scenarios. A few examples are the reliability, robustness, and the ability to work with other existing technologies, namely the interoperability and compatibility of such implementations. There have been several examples of communication failures between different first responder organizations in different disaster scenarios. For example at the World Trade Center on 9/11 some of the police warnings were not heard by firefighters resulting in several lives lost [5]. To address this problem, we propose a Hybrid Wireless Mesh Network (HWMN) as a candidate for highly reliable communication infrastructure capable of working in a heterogeneous environment with different available backhaul technologies for Internet connectivity. Also, cellular technology, as a pre-existing infrastructure, can be taken advantage of when the service is available in an emergency situation. We are using cellular simulators to study the possibilities of integrating cellular systems with other systems to evacuate people more efficiently in case of emergency and present alternative routes to avoid traffic congestion.

Wireless mesh networks (WMNs) are formed by self-organized wireless nodes that use multi-hop wireless relaying. These networks are useable in a variety of situations ranging from fixed residential broadband networking based on rooftop wireless mesh nodes to emergency response networks for handling large scale disasters. Quick deployability, minimal configuration, broadband communication, and easiness of reconfigurability are the major characteristics that make WMNs a suitable choice for emergency applications. There exist several open research issues in using such WMNs for emergency response applications. One example is the deployment strategy which must be in accordance with the principal application and its topological requirements. We, in this paper, present a hybrid distributed wireless networking architecture, extreme networking system (ENS), and present large set of performance observations collected from a real distributed hybrid wireless mesh network used for supporting a medical emergency response application. We present the traffic behavior observed in our network when a client server medical emergency response application is employed. The performance observations on real-traffic scenarios for emergency response application underlines the need for focusing further research on topology control, reliability, service availability, and distributed management.

The present paper replies to a comment by Nguyen et al. (IEEE Trans. Sel. Areas Commun., vol.24, no.12, p.2340-1, December 2006) on the original paper by Zorzi and Rao (IEEE Trans. Sel. Areas Commun., vol.12, no.8, p.1289-98, October 1994)

A variety of wireless interfaces are available for today's mobile user to access Internet content. When coverage areas of these different technologies overlap, a terminal equipped with multiple interfaces can use them simultaneously to improve the performance of its applications. In this paper, we motivate the advantages that can be had through simultaneous use of multiple interfaces and present a network layer architecture that enables diverse multiaccess services. In particular, we explore in depth one such service provided by the architecture: Bandwidth Aggregation (BAG) for real-time applications. An important aspect of the architecture when providing BAG services for real-time applications is the scheduling algorithm that partitions the traffic onto different interfaces such that the QoS requirements of the application are met. We propose one such algorithm Earliest Delivery Path First (EDPF), that ensures packets meet their playback deadlines by scheduling packets based on the estimated delivery time of the packets. We show through analysis that EDPF performs close to an idealized Aggregated Single Link (ASL) discipline, where the multiple interfaces are replaced by a single interface with same aggregated bandwidth. A prototype implementation and extensive simulations carried using video and delay traces show the performance improvement BAG with EDPF scheduling offers over using just the Highest Bandwidth Interface (HBI) and other scheduling approaches based on weighted round robin.

In this paper, we address the problem of energy efficient packet scheduling in a wireless environment. We consider a wireless transmitter which is limited by its finite battery resource. Our objective is to design a transmission schedule that maximizes battery lifetime subject to some delay constraints. To achieve this, we exploit two previously unconnected ideas: (i) channel coding can be used to conserve energy by transmitting at reduced power levels over longer durations; (ii) electro-chemical mechanisms in batteries allow them to recover energy during idle periods. While the first idea favors extending transmission durations, the second idea requires the transmitter to be idle to allow for recovery. In other words, bursty packet transmissions interspersed with idle periods extend battery life. Therefore, a strategy which is based entirely on either one or the other idea is not optimal. We provide a framework to merge the two ideas. We consider two kinds of delay constraints, one a deadline constraint and the other an average delay constraint and show that energy aware scheduling strategies for both these scenarios can result in significant energy savings.

In this paper we focus on routing strategies for wireless sensor networks over hop count (HC) virtual coordinates. We consider the problem of optimally delivering data packets by means of multi-hop forwarding techniques where we assume that each node in the network, upon the execution of a proper distribution algorithm, can obtain a hop count number, i.e., the minimum number of transmissions needed to get to the sink (destination) node on the shortest path. We exploit HCs in place of commonly considered geographical coordinates as a valuable indication of the direction towards the sink. Within this framework, we present localized greedy routing schemes and compare them against globally optimal solutions, where the objective is to minimize a properly defined cost function. Further, we present novel routing algorithms where the statistical knowledge of the minimum costs of second order (two hops away) neighboring nodes is used as an aid to drive the forwarding process. These statistically enhanced schemes are found to outperform both hop count greedy approaches and geographical routing of up to one order of magnitude in terms of goodness of the selected path

In wireless ad hoc networks, nodes communicate with far off destinations using intermediate nodes as relays. Since wireless nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. On the other hand, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios (complete cooperation and complete noncooperation) are inimical to the interests of a user. In this paper, we address the issue of user cooperation in ad hoc networks. We assume that nodes are rational, i.e., their actions are strictly determined by self interest, and that each node is associated with a minimum lifetime constraint. Given these lifetime constraints and the assumption of rational behavior, we are able to determine the optimal share of service that each node should receive. We define this to be the rational Pareto optimal operating point. We then propose a distributed and scalable acceptance algorithm called Generous TIT-FOR-TAT (GTFT). The acceptance algorithm is used by the nodes to decide whether to accept or reject a relay request. We show that GTFT results in a Nash equilibrium and prove that the system converges to the rational and optimal operating point.

We propose a distributed fair scheduling framework for wireless ad hoc networks. Unlike previous works, which assume error-free or predictable channels, our work is based on the signal-to-interference-plus-noise ratio (SINR) model and views channel errors as a result of the interference among the scheduled flows. We show by analysis that under the presented framework long term fairness is guaranteed; furthermore, the framework enables us to maximize throughput and minimize transmit power in a distributed manner.

We propose a distributed fair scheduling framework for wireless ad hoc networks. Unlike previous works, which assume error-free or predictable channels, our work is based on the signal-to-interference-plus-noise ratio (SINR) model and views channel errors as a result of the interference among the scheduled flows. We show by analysis that under the presented framework long term fairness is guaranteed; furthermore, the framework enables us to maximize throughput and minimize transmit power in a distributed manner.

A mobile terminal equipped with multiple interfaces can achieve a much higher bandwidth by aggregating the bandwidth offered by the individual networks. This helps support demanding applications like interactive video. Often, in spite of bandwidth aggregation, the available bandwidth may be too small to avoid frame loss altogether. Under these circumstances, it may be necessary to selectively discard frames to minimize the effect of their loss on the overall video quality. In this paper, we consider different frame discard algorithms and study their performance in the presence of multiple interfaces. We show through trace driven simulations that attempting to transmit every frame results in severe performance degradation. In particular we show that our proposed algorithm MC-drop outperforms other algorithms in terms of suitably defined metrics that capture overall video quality.

In this paper we study the multihop performance of two energy efficient forwarding schemes (GeRaF and GAF) in a Rayleigh fading propagation scenario. Specifically, we evaluate the number of hops which are necessary to reach a destination at distance D, as a function of the density of available relay nodes. Analytical and simulation results show that GeRaF significantly outperforms GAF from the multihop point of view. GeRaF's energy/latency performance is also found to be very robust with respect to propagation impairments.

We consider the design of error control schemes in wireless sensor networks. Unlike in traditional communications systems, in which coding is almost always beneficial, in sensor networks, the relatively short communications range and the lack of energy resources may lead to different conclusions. In particular, the energy spent for decoding may actually exceed that saved due to the coding gain. In this environment, interesting tradeoffs can be identified and non-traditional ways to perform error control may be proposed.

We show that significant performance improvements are obtained by introducing time-divisioning in the bit-loading algorithms for discrete multitone (DMT) systems. DMT modulation is used in both wired and wireless multiuser, multicarrier systems. Allocation of power among the different users and subchannels, so as to optimize the user data rates, is an important problem. Existing algorithms allow users to transmit together in a given subchannel even when the users are strongly coupled in that subchannel. We propose to use time-divisioning to separate the transmissions of users in subchannels in which they are heavily coupled, while allowing them to transmit together in subchannels where they are lightly coupled. We show that significant improvements in system performance are possible using the proposed scheme, especially at higher values of coupling coefficients.

In this paper, we address the problem of energy efficiency in wireless ad hoc networks. We consider an ad hoc network comprising a set of sources, communicating with their destinations using multiple routes. Each source is associated with a utility function which increases with the total traffic flowing over the available source-destination routes. The network lifetime is defined as the time until the first node in the network runs out of energy. We formulate the problem as one of maximizing the sum of the source utilities subject to a required constraint on the network lifetime. We present a primal formulation of the problem, which uses penalty functions to take into account the system constraints, and we introduce a new methodology for solving the problem. The proposed approach leads to a flow control algorithm, which provides the optimal source rates and can be easily implemented in a distributed manner. When compared with the minimum transmission energy routing scheme, the proposed algorithm gives significantly higher source rates for the same network lifetime guarantee.

In this paper, a model for N mobile nodes that talk to one another simultaneously is considered under the following constraint: No node may transmit and receive at the same time. Furthermore, we focus on a personal area network (PAN) application limiting the network to a single-hop ad-hoc network. The resulting half-duplex wireless network is an interesting special case of the general full-duplex multihop ad-hoc networks. We model the system of the wireless channel and the N nodes as an N /spl times/ N switch. We call a PAN based on this model a switched PAN (S-PAN). The model is motivated by some limitations of the current specification of Bluetooth and by recent amendments of the rules governing the free-license ISM bands by the Federal Communications Commission. A specific Bluetooth-based S-PAN network that requires minimal changes to the current Bluetooth specification is introduced. The Bluetooth-based S-PAN is shown to outperform the current Bluetooth specification in throughput, delay, and energy-fairness to masters. Specifically, the S-PAN piconet is shown to achieve a throughput of up to 5 times (and possibly higher) the throughput of an equivalent Bluetooth piconet.

We study a novel forwarding technique based on the geographical location of the nodes involved and random selection of the relaying node via contention among receivers. We focus on the multihop performance of such a solution, in terms of average number of hops to reach a destination as a function of the distance and of the average number of available neighbors. An idealized scheme (in which the best relay node is always chosen) is discussed, and its performance is evaluated by means of both simulation and analytical techniques. A practical scheme to select one of the best relays is shown to achieve performance very close to that of the ideal case.

This paper addresses the problem of power control in ad hoc networks supporting multicast traffic. First, we present a distributed algorithm which, given the set of multicast transmitters and their corresponding receivers, provides an optimal solution to the power control problem, if there is any. The transmit power levels obtained by solving the optimization problem minimize the network power expenditure while meeting the requirements of the SNR at the receivers. Whenever no optimal solution can be found for the given set multicast transmitters, we introduce a joint scheduling and power control algorithm, which eliminates the strong interferers thus allowing the other transmitters to solve the power control problem. The algorithm can be implemented in a distributed manner; however, it provides a sub-optimal solution since it is based on local information. Simulation results show that the obtained solution is close to the global optimum, when it exists. When there is no optimal solution, the proposed algorithm tries to maximize the number of successful multicast transmission.

In wireless ad hoc networks, nodes communicate with far off destinations using intermediate nodes as relays. Since wireless nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. On the other hand, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios (complete cooperation and complete noncooperation) are inimical to the interests of a user. In this paper we address the issue of user cooperation in ad hoc networks. We assume that nodes are rational, i.e., their actions are strictly determined by self interest, and that each node is associated with a minimum lifetime constraint. Given these lifetime constraints and the assumption of rational behavior, we are able to determine the optimal throughput that each node should receive. We define this to be the rational Pareto optimal operating point. We then propose a distributed and scalable acceptance algorithm called generous tit-for-tat (GTFT). The acceptance algorithm is used by the nodes to decide whether to accept or reject a relay request. We show that GTFT results in a Nash equilibrium and prove that the system converges to the rational and optimal operating point.

In this paper, we describe a novel forwarding technique based on geographical location of the nodes involved and random selection of the relaying node via contention among receivers. A collision avoidance scheme based on this idea is described in detail, and an approximate analysis is provided. The proposed scheme is compared with STEM, and is shown to perform significantly better for sufficient node density.

In this paper, we propose a novel forwarding technique based on geographical location of the nodes involved and random selection of the relaying node via contention among receivers. We focus on the multihop performance of such a solution, in terms of the average number of hops to reach a destination as a function of the distance and of the average number of available neighbors. An idealized scheme (in which the best relay node is always chosen) is discussed and its performance is evaluated by means of both simulation and analytical techniques. A practical scheme to select one of the best relays is shown to achieve performance very close to that of the ideal case. Some discussion about design issues for practical implementation is also given.

In this paper, we study a novel forwarding technique based on geographical location of the nodes involved and random selection of the relaying node via contention among receivers. We provide a detailed description of a MAC scheme based on these concepts and on collision avoidance and report on its energy and latency performance. A simplified analysis is given first, some relevant trade offs are highlighted, and parameter optimization is pursued. Further, a semi-Markov model is developed which provides a more accurate performance evaluation. Simulation results supporting the validity of our analytical approach are also provided.

Wireless technologies sharing the same frequency band and operating in the same environment often interfere with each other, causing severe decrease in performance. We propose two coexistence mechanisms based on traffic scheduling techniques that mitigate interference between different wireless systems operating in the 2.4-GHz industrial, medical, and scientific band. In particular, we consider IEEE 802.11 wireless local area networks (WLANs) and Bluetooth (BT) voice and data nodes, showing that the proposed algorithms can work when the two systems are able to exchange information as well as when they operate independently of one another. Results indicate that the proposed algorithms remarkably mitigate the interference between the IEEE 802.11 and BT technologies at the expense of a small additional delay in the data transfer. It is also shown that the impact of the interference generated by microwave ovens on the IEEE 802.11 WLANs performance can be significantly reduced through the mechanisms presented.

We develop a novel approach for conserving energy in battery-powered communication devices. There are two salient aspects to this approach. First, the battery-powered devices move through multiple, progressively deeper, sleep states in a predictable manner. Nodes in deeper sleep states consume lower energy while asleep, but incur a longer delay and higher energy cost to awaken. Second, the nodes are woken up on demand through a paging signal. To awaken nodes that are in deep sleep, the paging signal has to be decoded using very low power circuits such as those used in radio frequency tags. To accommodate this need, in a manner that scales well with the number of nodes, the number of distinct paging signals has to be much less than the number of possible nodes. This is accomplished through a group-based wakeup scheme, which initially awakens the targeted node along with a number of other similarly disposed nodes that subsequently return to their original sleep state. Tradeoffs among energy consumption, delay and overhead are presented; comparisons with other protocols show the potential for 16% to 50% improvement in energy consumption.

This paper proposes a new packet rate scheduling scheme for a non-real time data service over the uplink of a burst switching-based direct sequence code division multiple access (DS/CDMA) system to support the integrated voice/data service. We consider the most general form of optimization problem formulation to determine the optimal number of transmission-time groups along with their data rates, which minimize the average packet transmission delay. An ordered packet length-based group-wise transmission (OLGT) scheme is proposed as a simple heuristic solution approach to this problem and present some analytical results for performance comparison with other possible schemes.

Different wireless systems sharing the same frequency band and operating in the same environment are likely to interfere with each other and experience a severe decrease in throughput. We consider IEEE 802.11 WLANs and Bluetooth-based WPANs, which operate in the 2.4 GHz ISM bands. We propose two coexistence mechanisms based on traffic scheduling techniques, which mitigate interference between the two technologies. The proposed algorithms can be applied either when 802.11 and Bluetooth are able to exchange information as well as when they operate independently of one another. Results show that through the proposed coexistence mechanisms the interference between 802.11 and Bluetooth can be reduced and the throughput of the two systems is significantly improved at the expense of a small additional delay in the transfer of data traffic.

In this paper, we address the problem of energy efficient packet scheduling in a wireless environment. We consider a wireless transmitter which is limited by its finite battery resource. Our objective is to design a transmission schedule that maximizes battery lifetime subject to some delay constraints. To achieve this, we exploit two previously unconnected ideas: (i) channel coding can be used to conserve energy by transmitting at reduced power levels over longer durations; (ii) electro-chemical mechanisms in batteries allow them to recover energy during idle periods. While the first idea favors extending transmission durations, the second idea requires the transmitter to be idle to allow for recovery. Therefore, a strategy which is based entirely on either one or the other idea is not optimal. We provide a framework to merge these two ideas. We consider two kinds of delay constraints, one a deadline constraint and the other an average delay constraint and show that energy aware scheduling strategies for both these scenarios can result in significant energy savings.

In this paper, we address the problem of energy efficiency in ad hoc wireless networks. We consider a network that is shared by a set of sources, each one communicating with its corresponding destination using multiple routes. Each source is associated with a utility function which increases with the total traffic flowing over the available source-destination routes. The network lifetime is defined as the time until the first node in the network runs out of energy. We formulate the problem as one of maximizing the sum of the sources' utilities subject to the required constraint on network lifetime. We present a primal formulation of the problem, which uses penalty functions to take into account the system constraints, and we introduce a new methodology for solving the problem. The proposed approach leads to a flow control algorithm, which provides the optimal sources' rate and can be easily implemented in a distributed manner. When compared with the minimum transmission energy routing scheme, the proposed algorithm gives significantly higher sources' rates for same network lifetime guarantee.

In wireless ad hoc networks, nodes communicate with far off destinations using intermediate nodes as relays. Since nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. However, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios (complete cooperation and complete non-cooperation) are inimical to the interests of a user. In this paper, we address the issue of user cooperation in ad hoc networks. We assume that nodes are rational, i.e. their actions are strictly determined by self-interest, and that each node is associated with a minimum lifetime constraint. Then, we are able to determine the optimal throughput that each node should receive, and we define this to be the rational Pareto optimal operating point. We propose a distributed and scalable acceptance algorithm, which is used by the nodes to decide whether to accept or reject a relay request. The algorithm results in a Nash equilibrium, and we prove that the system converges to the rational and optimal operating point.

With the emergence of different wireless technologies, a mobile terminal equipped with multiple interfaces can achieve a much higher bandwidth by aggregating the bandwidth offered by the individual networks. In this paper, we present a system based on Mobile IP that achieves the above objective. We discuss in detail the architectural requirements and algorithms that are needed to support the system.

The need for network processors capable of forwarding IP packets at OC-192 and higher data rates has been well established. At the same time, there is a growing need for complex tasks, like packet classification and differentiated services, to be performed by network processors. At OC-768 data rate, a network processor has 9 nanoseconds to process a minimum-size IP packet. Such ultra high-speed processing, involving complex memory-intensive tasks, can only be achieved by multi-CPU distributed memory systems, using very high performance on-chip communication architectures. In this paper, we propose a novel communication network architecture for 8-CPU distributed-memory systems that has the potential to deliver the throughput required in next generation routers. We then show that our communication architecture can easily scale to accommodate much greater number of network nodes. Our network architecture yields higher performance than the traditional bus and crossbar yet has low implementation cost. It is quite flexible and can be implemented in either packet or circuit switched mode. We will compare and contrast our proposed architecture with busses and crossbars using metrics such as throughput and physical layout cost.

In this paper we develop a novel approach to conserving energy in battery powered communication devices. There are two salient aspects to this approach. First, the battery powered devices move through multiple, progressively deeper, sleep states in a predictable manner. Nodes in deeper sleep states consume lower energy while asleep but incur a longer delay and higher energy cost to wake up. Second, the nodes are woken up on demand through a paging signal. To awaken nodes that are in deep sleep, the paging signal has to be decoded using very low power circuits such as those used in RF tags. To accommodate this need, in a manner that scales with with the number of nodes, the number of distinct paging signals has to be much less than the number of possible nodes. This is accomplished through a group based wake up scheme, that initially awakens the targeted node along with a number of other similarly disposed nodes that subsequently return to their original sleep state. Trade-offs among energy consumption, delay as well as overhead are presented; comparisons with other protocols show the potential for 16 to 50% improvement in energy consumption.

A challenging aspect of mobile communications consists in exploring ways in which the available run time of terminals can be maximized. We present a detailed electrochemical battery model and a simple stochastic model that captures the fundamental behavior of the battery. The stochastic model is then matched to the electrochemical model and used to investigate battery management techniques that may improve the energy efficiency of radio communication devices. We consider an array of electrochemical cells. Through simple scheduling algorithms, the discharge from each cell is properly shaped to optimize the charge recovery mechanism, without introducing any additional delay in supplying the required power. Then, a battery management scheme, which exploits knowledge of the cells' state of charge, is implemented to achieve a further improvement in the battery performance. In this case, the discharge demand may be delayed. Results indicate that the proposed battery management techniques improve system performance no matter which parameters values are chosen to characterize the cells' behavior.

We present a new approach to minimizing energy consumption by addressing battery management techniques that exploit the charge recovery effect inherent to many secondary storage batteries. We review results that pertain to the capacity of a battery and its dependence on the intensity of the discharge current. The phenomenon of charge recovery that takes place under bursty or pulsed discharge conditions is identified as a mechanism that can be exploited to enhance the capacity of a battery. The bursty nature of many data traffic sources suggests that data transmissions may provide natural opportunities for charge recovery. We explore stochastic models to track charge recovery in conjunction with bursty discharge processes. Using the postulated model, we identify the improvement to battery capacity that results from a pulsed discharge driven by bursty stochastic discharge demand. The insight from this analysis leads us to propose discharge shaping techniques that trade-off energy efficiency with delay.

A challenging aspect of mobile communications consists of exploring ways in which the available run time of the terminals can be maximized. In this paper we investigate battery management techniques that can dramatically improve the energy efficiency of radio communication devices. We consider an array of electrochemical cells connected in parallel. Through simple scheduling algorithms the discharge from each cell is properly shaped to optimize the charge recovery mechanism, without introducing any additional delay in supplying the required power. Then, a traffic management scheme, that exploits the knowledge of the cells' state of charge, is implemented to achieve a further improvement in the battery performance. In this case, the discharge demand may be delayed. Results indicate that the proposed battery management techniques improve system performance no matter which parameter values are chosen to characterize the cell behavior.

The coexistence of different wireless systems that share the same frequency band is becoming one of the most challenging issue due to the wide-spread popularity of WLANs and to the rapid development of short-range radio systems. In this paper we consider WLANs based on the IEEE 802.11 standard and a short-range radio system based on Bluetooth specifications, which operate in the 2.4 GHz ISM frequency band. We present a model of the interference that IEEE 802.11 WLANs may experience either because of a voice or a data Bluetooth link. We derive results showing that by applying simple traffic shaping techniques, interference can be significantly reduced. In the presence of Bluetooth data traffic, WLAN packet error probability can be decreased by 1996 at the expense of an additional average delay in Bluetooth packet transmission equal to 10 ms, or by 2946 at the expense of a Bluetooth average packet delay equal to 110 ms.

This paper presents a power management scheme that maximizes energy saving in wireless ad hoc networks while still meeting the required quality of service (QoS). We assume that battery-powered devices can be remotely activated by a waking-up signal using a simple circuit based on RF tag technology. In this way, devices that are not currently active may enter a sleep state and power up only when they have pending traffic. Radio devices select different time-out values, so called sleep pattern, to enter various sleep states depending on their battery status and quality of service. The performances of the proposed policy are derived by simulation for a simple ad hoc network scenario. Results show the achieved tradeoff between power saving and traffic delay.

To determine the end-to-end delay in block coded transmission over the Gilbert-Elliott (1960, 1963) channel with interleaving and a retransmission strategy, the probability distribution of the number of transmissions that a packet has to go through before it succeeds has to be found. We propose an approximate method to evaluate the distribution when the error statistics are dependent. The end-to-end delay is then examined. Our study provides a way to choose an error-control scheme (i.e., an interleaver of an appropriate size with a retransmission protocol), which meets both the delay constraint and a reliability requirement.

In an effort to conserve energy, mobile hosts wake up periodically to serve incoming traffic. This gives rise to a trade-off between energy consumption and delay. However, the deterministic strategy of current systems might not yield the desired performance. We show that knowledge of the statistical characteristics of incoming traffic can be used to better meet the energy and delay requirements of the mobile node. We consider zero-buffer and buffered models. We propose some strategies to improve the energy efficiency and study the related trade-offs. We also introduce a new metric for energy efficiency and derive explicit expressions for the same. Our results prove that significant gains accrue by employing intelligent wake-up schemes.

In this paper, we propose and study a multi-rate resource control (MRRC) scheme for non-real time data applications in mobile cellular networks. The MRRC scheme adapts to dynamically changing system load by adjusting resource assignments for mobiles. The MRRC scheme consists of four major techniques: 1) variable-rate admission control policy; 2) soft handoff procedure; 3) resource assignment prioritization based on mobile's location, non-handoff versus handoff zone; 4) handoff prioritization by queuing handoff requests. We evaluate the blocking probability and the forced termination probability. In addition, we study the effect of handoff to cell area ratio (HTCR) on MRRC performance. A streamlined analytical model is introduced to evaluate the MRRC scheme for the 2-cells case. Numerical results are presented for the 2-cells case; simulation results are presented for the 10-cells case. Our results show that the MRRC system achieves significant gain over the conventional single rate system in terms of the blocking probability and the forced termination probability.

The overall objective of this work is to explore ways in which the energy efficiency of communications can be enhanced through the use of communication protocols that exploit the charge recovery mechanism inherent to many secondary storage batteries.In the first part of this paper, we summarize the behavior of electrochemical energy cells.We compile results that pertain to the capacity of a cell and its dependence on the intensity of the discharge current.The phenomenon of charge recovery that takes place under bursty or pulsed discharge conditions is identified as a mechanism that can be exploited to enhance the capacity of a cell.The bursty nature of many data trafllc sources suggests that there may be a natural fit between the two.In the second part of this manuscript, we explore thii synergy by developing a stochastic model that tracks charge recovery in conjunction with bursty discharges due to transmissions driven by Bernoulli arrivals.We derive the resulting capacity advantage relative to constant discharge as a function of the burstiness of the arrival for two discharge scenarios.

This paper introduces a stochastic model of battery behavior, that emulates electrochemical mechanisms that are key to battery performance under pulsed discharge conditions. A pulsed discharge allows charge recovery during the idle periods. Recovery depends on the state of charge of the battery and on the duration of the rest time period. Using the postulated model, we derive the improvement to battery lifetime that results from pulsed current discharge driven by bursty stochastic transmissions. The results emphasize the role of traffic shaping in the quest to enhance battery behavior.

In this paper, we study the performance of a simple retransmission-based error-control strategy for delay-constrained data communications over a bursty channel. Correlated errors are modeled as a two state Markov process. A retransmission algorithm is used to correct errors, and the probability that a packet is not successfully delivered within D slots of its arrival is computed. In the presence of a smoothing buffer at the receiver, this is the probability that the jitter experienced by a packet is too large to be absorbed by the buffer itself. The cases of zero and nonzero roundtrip delay are studied separately, as are the conditions of perfect and imperfect feedback. Our results relate the achievable quality of service and the amount of traffic that can be served to the packet-error process parameters, which in turn are induced by the physical layer specifications. This relationship between the traffic and the channel parameters can be useful in making admission control decisions and in assessing the effect of physical layer design on the performance of higher layer protocols.

In this paper, the bulk throughput performance of TCP NewReno over wireless fading links having memory is studied. Like TCP Tahoe, the NewReno version of TCP implements a fast retransmit procedure, but it uses a different congestion window adaptation algorithm. In this study, we show that, for the default parameters of the BSD implementation of TCP over a 1.5 Mbps wireless link having a very small bandwidth-delay product, and as long as sufficiently large advertised window sizes are used, the burstiness in packet errors caused by slow multipath fading (experienced by slow moving users) significantly benefits NewReno compared to i.i.d. packet errors (experienced at vehicular user speeds). We further show that, in such slow fading conditions, NewReno performs no better than Tahoe, mainly due to the high degree of correlation in the fading process.

We present techniques to capture the behavior of realistic channels with mathematically tractable models, We examine different state-space aggregation techniques to reduce a large number of states of Markov chain to a fewer number of states, The property of strong and weak lumpability is discussed and the stochastic bounding techniques are examined. These techniques are applied to three different types of previously published channel models for mobile VHF, wireless indoor, and Rayleigh fading channels. Results show that our stochastic bounding technique can produce a simpler yet still accurate upper bound the for original channel model. We find that the bounds perform well when the higher-layer error control protocols such as stop-and-go and TCP are considered.

We are concerned with the performance at the media access control (MAC) layer of the protocol stack when multibeam adaptive antenna arrays are employed at the base station site. Specifically, we analyze the performance of slotted ALOHA when the base station receiver uses multibeam antenna arrays capable of steering the beams selectively on smaller sectors. The effect of different beamwidths, number of beams, beam steering patterns, and beam service times on the achieved throughput-delay performance of slotted-ALOHA is evaluated. It is observed that under high load conditions steered beams with long beam service times offer better performance, whereas under light load conditions static coverage patterns are better.

There has been an emerging interest in using ATM for wireless transmissions. Because ATM is primarily designed for a rather benign error free environment, in the wireless context the sources of errors and their consequences must be thoroughly understood. While this concern is valid in any network, it takes on a new more central role in the mobile wireless environment, where error bursts are expected to be a very significant source of degradation. These concerns motivate this study of the impact of errors on ATM cell transfer in the wireless environment. In this paper, we examine the impact of burst errors on the direct transfer of ATM cells taking into account the cell framing format. We examine the consequences of interleaving as well as the impact of fading. We find that fragmenting the data in cells could result in a much higher error rate as seen by the higher layers relative to the bit error rate on the raw channel.

We investigate the behavior of block errors which arise in data transmission on fading channels. Our approach takes into account the details of the specific coding/modulation scheme and tracks the fading process symbol by symbol. It is shown that a Markov approximation for the block error process (possibly degenerating into an identically distributed (i.i.d.) process for sufficiently fast fading) is a good model for a broad range of parameters. Also, it is observed that the relationship between the marginal error rate and the transition probability is largely insensitive to parameters such as block length, degree of forward error correction and modulation format, and depends essentially on an appropriately normalized version of the Doppler frequency. This relationship can therefore be computed in the simple case of a threshold model and then used more generally as an accurate approximation. This observation leads to a unified approach for the channel modeling, and to a simplified performance analysis of upper layer protocols.

We consider the problem of communications over a wireless channel in support of data transmissions from the perspective of small portable devices that must rely on limited battery energy. We model the channel outages as statistically correlated errors. Classic ARQ strategies are found to lead to a considerable waste of energy, due to the large number of transmissions. The use of finite energy sources in the face of dependent channel errors leads to new protocol design criteria. As an example, a simple probing scheme, which slows down the transmission rate when the channel is impaired, is show? to be more energy efficient, with a slight loss in throughput. A modified scheme that yields slightly better performance but requires some additional complexity is also studied. Some references on the modeling of battery cells are discussed to highlight the fact that battery charge capacity is strongly influenced by the available "relaxation time" between current pulses. A formal approach that can track complex models for power sources, including dynamic charge recovery, is also developed.

In the development of encoding algorithms for image, video, and other mixed media transmissions, it is important to note that the channel "seen" by the applications is the physical channel as modified by the error-correcting mechanisms used at the physical level. Therefore, the statistics of the residual error process is relevant to the design of encoding algorithms. In this paper, we study the second- and third-order statistics of the residual error process when block transmissions are performed over a bursty channel. The effect of interleaving is explicitly studied. The conditions under which a Markovian model for the block errors is adequate are identified. Derivations of the parameters of the block error process are then presented in terms of the parameters of the bit/symbol error process. At higher data speeds an effective interleaving strategy is found to require a very large buffer.

We investigate the behavior of block errors which arise in data transmission on fading channels. Our approach is more detailed than previous studies, in that it takes into account the specific coding/modulation scheme and it tracks the fading process symbol by symbol. It is shown that a Markov approximation for the block error process (possibly degenerating into an i.i.d. process for sufficiently fast fading) is a very good model for a broad range of parameters. Also, it is observed that the relationship between the marginal error rate and the transition probability is largely insensitive to parameters such as block length, degree of forward error correction and modulation format, and only depends on an appropriately normalized version of the Doppler frequency. This observation leads to a unified approach for the channel modelling which simplifies the performance analysis of upper-layer protocols.

In this paper, we study the delay performance of a circuit switched, self-routing Delta network. A gated hold protocol that retains partial path information is used to guarantee service of all requests. A novel technique that involves the construction of an easier to analyze dominant system is presented. A recursive expression for the probability mass function of the cycle time in the dominant system is derived. Comparison of the dominant system analysis with simulation of the actual system shows that the dominant system accurately predicts performance for low network loads. As network loads increase, the dominant system becomes worse at predicting behavior of the actual system. These results also help develop insight into how to trade off higher delay variability for increased throughput.

An automatic-repeat-request (ARQ) Go-Back-N (GBN) protocol with unreliable feedback and time-out mechanism is studied, using renewal theory. Transmissions on both the forward and the reverse channels are assumed to experience Markovian errors. The exact throughput of the protocol is evaluated, and simulation results, that confirm the analysis, are presented. A detailed comparison of the proposed method and the commonly used transfer function method reveals that the proposed approach is simple and potentially more powerful.

The authors analyze a circuit-switched, blocking, multi-stage interconnection network (MIN) with arbitrary independent input distributions and arbitrary switch routing probabilities. The network uses a gated-hold strategy which retains partial path information. By formulating a dominant system, they derive a recursive expression for the mean time to process a batch of requests given a particular input distribution and a set of switch routing probabilities. This system is compared to a simulation of a non-blocking switch implementing a similar gated strategy. Results indicate that this method yields tight bounds for small networks with arbitrary input distributions and switch routing probabilities. For networks with uniform input and output distributions this bound is closer than one introduced in a previous work examining the same protocol.>

We consider the slotted ALOHA protocol with capture, in a mobile communication environment, in the presence of Rayleigh fading and log-normal shadowing. The capture probabilities and their asymptotic value, as the number of colliding packets tends to infinity, are computed. A sufficient condition, under which this limit is positive, is identified and expressed in terms of the spatial distribution of the users. Also, various models for this latter distribution are discussed. These results help identify the region in which the system may achieve a positive stable throughput. Finally, a retransmission control scheme, that enhances the throughput, is considered, and the stability of the system is rigorously proven. We also show that the use of retransmission control is unavoidable if the network performance predicted in some recent literature is to be achieved.>

The authors study the effect of burstiness of packet arrivals on the performance of a buffered finite-user random-access system. Primarily, they formulate and analyze a protocol that exploits the burstiness of arrivals and the presence of buffers. In addition, it is shown that the boundary of the region in which infinite user models best approximate a finite-user system is dependent on the burstiness of the arrival process. They also show that an accurate comparison between time-division multiaccess (TDMA) and random-access schemes depends crucially on the number of users in the system.>

A method for deriving the stability conditions of limited service token ring systems is presented. The idea is to introduce a sequence of auxiliary systems that dominate the actual system in a well-defined sense. The stability region is derived without resorting to stationarity assumptions. Thus, it is possible to derive inner bounds for the stability region.>

A random multiple-access system which employs a collision resolution algorithm for accessing a common time-varying channel is considered. The channel is assumed to be in one of two states. In each state, the channel is characterized by a general discrete memoryless channel and the transitions between the two states are assumed to be Markovian. A set of sufficient conditions for the ergodicity (stability) of the system is established. As an example, the case when the Capetanakis tree algorithm operates with a time-varying noisy channel is examined. The stability of this system is analyzed, and the throughput is evaluated.>

A random multiple access system with a finite population of buffered, asymmetric users is studied. An upper bound is found to the mean total delay experienced by a user, including the queuing delay. The analysis facilitates an understanding of the interrelationship among delay, burstiness, the degree of asymmetry, and the number of users. The role of asymmetry is also studied and it is shown that the delay in an asymmetric system is smaller than the delay in a symmetric system for the same total arrival rate.>

A random multiple-access system which uses a collision resolution algorithm for accessing a common time-varying channel is considered. The channel is assumed to be in one of two states. In each state the channel is characterized by a general discrete memoryless channel, and the transitions between the two states are assumed to be Markovian. A set of sufficient conditions for the ergodicity (stability) of the system is established. As an example, the case when the Capetanakis tree algorithm operates with a time-varying noisy channel is examined. The stability of this system is analyzed and the throughput is evaluated.>

The standard discrete-time slotted ALOHA system with a finite number of buffered terminals is considered. The stability (ergodicity) region for this system is known only for the case of two terminals and for the case of any number of symmetric terminals. The stability of the system is studied by means of a simple concept of dominance. It is shown that the stability region for the case of two terminals can be obtained in a simple way. Lower (inner) bounds are obtained for the stability region of the system with an arbitrary finite number of terminals that are tighter than the ones already known. A similarity between these stability results and the achievable region of the no-feedback collision channel is pointed out that suggests a connection between the two problems.>

A decentralized multiple access system in whichm \geq 2collided users employ a random access protocol is considered. Maximum entropy considerations are used to select the appropriate timeout distribution under various moment constraints. This analysis extends and corrects an earlier result form = 2.