Emergent effect is crucial to understanding the properties of complex systems that do not appear in their basic units, but there has been a lack of theories to measure and understand its mechanisms. In this letter, we consider emergence as a kind of structural nonlinearity, discuss a framework based on homological algebra that encodes emergence as the mathematical structure of cohomologies, and then apply it to network models to develop a computational measure of emergence. This framework ties the potential for emergent effects of a system to its network topology and local structures, paving the way to predict and understand the cause of emergent effects. We show in our numerical experiment that our measure of emergence correlates with the existing information-theoretic measure of emergence.

Data reporting strategy in heterogeneous wireless sensor networks can be differentiated based on task-specific requirements. In this paper, we propose a novel two-phase data reporting (TDR) scheme that supports class-based QoS to sensor nodes in different priority classes. In the first phase, time slots are divided into separate data reporting round defined for each class, while in the second phase, the sensor nodes in the same class are scheduled to particular time slots depending on the given number of slots calculated in the first phase. In TDR, sensor nodes compete with other nodes in the same class only, while nodes in different classes have differentiated channel access opportunity. TDR is performed in a single-hop cluster-based topology, and a cluster head acts as a node assignment manager (NAM). Sensor nodes wake up for their scheduled time slots; otherwise, they go into sleep mode to save energy. TDR supports both schedule- based and contention-based channel access mechanisms and is scalable due to its distributed nature.

In standard IEEE 802.11 based systems, when the wireless client migrates away from the radio range of the currently associated access point (AP), network applications temporarily loose connectivity till the client is able to re-associate itself with a new AP. The delay that occurs during the break-off interval can vary from a few hundreds of microseconds to a few seconds. However, delay sensitive applications such as Voice over IP (VoIP) or streaming multimedia applications usually are unable to tolerate such long connectivity delays that fall beyond the range of 50 - 200 ms. This results in dropped calls or frozen video frames. In this paper we describe the design, implementation, and evaluation of a software based framework that facilitates seamless and transparent handoff between different APs in standard IEEE 802.11 based wireless local area networks (WLANs). Although different solutions are available in the literature that seek to address the handoff latency, most of them propose changes that are outside the purview of the current 802.11 standards. We have specifically kept such compatibility restrictions in mind and have devised a software based client side solution that is capable of reducing handoff delays to an average value of 20 ms. It is available as a driver update to the client and requires no additional support from the network. As part of our solution, we have successfully implemented and tested our proposed solution framework on Atheros AR5212 chipsets using the open source MadWifi driver.

In networks carrying large volume of traffic, accurate traffic characterization is necessary for understanding the dynamics and patterns of network resource usage. Previous approaches to flow characterization are based on random sampling of the packets (e.g., Cisco's NetFlow) or inferring characteristics solely based on long lived flows (LLFs) or on lossy data structures (e.g., bloom filters, hash tables). However, none of these approaches takes into account the heavy-tailed nature of the Internet traffic and separates the estimation algorithm from the flow measurement architecture.In this paper, we propose an alternate approach to traffic characterization by closely linking the flow measurement architecture with the estimation algorithm. Our measurement framework stores complete information related to short lived flows (SLFs) while collecting partial information related to LLFs. For real-time separation of LLFs and SLFs, we propose a novel algorithm based on typical sequences from information theory. The distribution (pdf) and sample space of the underlying traffic is estimated using the non-parametric Parzen window technique and likelihood function defined over the Coupon collector problem. We validate the accuracy and performance of our estimation technique using traffic traces from the internal LAN in our laboratory and from National Library for Applied Network Research (NLANR).

Fluctuations in protein number (noise) caused by the stochasticity in gene expression plays a central role in the dynamic behavior of cellular pathways. Deterministic models capture average cell population behavior and are limited in their relevance in modeling stochastic deviations of gene expression in single cells. In this paper, we develop a birth and death Markov chain model to capture the discrete molecular events of transcription and translation in prokaryotic cells. We derive mathematical models for the expression `burst frequency' distribution as well as the number of protein molecules per burst. We validate our stochastic models with recent single cell experiments on the lacZ gene in Escherichia Coli. Further, we build a discrete-event stochastic simulation system to study the transient dynamics of lacZ gene expression, quantifying the role of promoters in controlling the `burstiness' of protein synthesis.

This paper presents a parametric model to estimate the DNA-protein binding time using the DNA and protein structures and details of the binding site. To understand the stochastic behavior of biological systems, we propose an "in silico" stochastic event based simulation that determines the temporal dynamics of different molecules. This paper presents a parametric model to determine the execution time of one biological function (i.e. simulation event): protein-DNA binding by abstracting the function as a stochastic process of microlevel biological events using probability measure. This probability is coarse grained to estimate the stochastic behavior of the biological function. Our model considers the structural configurations of the DNA, proteins and the actual binding mechanism. We use a collision theory based approach to transform the thermal and concentration gradients of this biological process into the probability measure of DNA-protein binding event. This information theoretic approach significantly removes the complexity of the classical protein sliding along the DNA model, improves the speed of computation and can bypass the speed-stability paradox. This model can produce acceptable estimates of DNA-protein binding time to be used by our event-based stochastic system simulator where the higher order (more than second order statistics) uncertainties can be ignored. The results show good correspondence with available experimental estimates. The model depends very little on experimentally generated rate constants

The ever-growing demand of network capacity has resulted in the inception of optical burst switching (OBS), offering all-optical transmission, high-speed data rates, and format-transparent switching. However, the current OBS architecture is very complex, requiring costly fiber delay lines and quality-of-service (QoS) management techniques. In this paper, we propose a new OBS architecture based on photonic container switching to be deployed in the core network. We show that our architecture will solve most of the complexities of existing OBS mechanisms and, in fact, will make the core an all-optical zero-packet-loss network that will also guarantee equal QoS to all of the users. The packets are actually packed in fixed-size containers, which will be converted into an optical burst and transmitted through the network. Obviously, a major issue to solve in our architecture is the scheduler design that ensures zero packet loss and no optical-to-electrical switchings in the intermediate nodes. We devise a divide-and-conquer solution for the scheduler design problem and present some efficient algorithms for the same. We also analyze the performance of our algorithms under varying traffic conditions and network topologies to ascertain their efficiency and robustness.

Rapid advances in a wide range of wireless access and networking technologies, along with ubiquitous computing and communications, have set the stage for the development of smart environments (for example, smart homes or offices). "Context awareness" is perhaps the most salient feature in such intelligent (indoor) environments. Examples of contexts include the "location" and "activities" of the inhabitants among others. In this paper, we develop a predictive framework for location-aware resource optimization in smart homes based on the hypothesis that the mobility of an inhabitant creates an uncertainty of his location. With the help of information theory, the proposed framework is shown to minimize this uncertainty through optimal learning and prediction of the inhabitant's movement (location) profiles captured in the symbolic domain. The concept of the asymptotic equipartition property (AEP) is also used to predict the inhabitant's most likely routes (or path-segments) with a high degree of accuracy. Successful predictions help in several ways, such as automated device control and proactive reservation of resources (for example, electrical energy and other utilities or scarce wireless bandwidth for mobile multimedia applications) along the inhabitant's most probable locations and routes. The goal here is to minimize the maintenance and operations cost of the smart home, as well as to provide better comfort to the inhabitants. Experimental results from a typical smart home floor plan corroborate the prediction success and significant reduction in daily energy consumption and manual operations of devices.

Today's distributed computing systems incorporate different types of nodes with varied bandwidth constraints which should be considered while designing cost-optimal job allocation schemes for better system performance. In this paper, we propose a fair pricing strategy for job allocation in bandwidth-constrained distributed systems. The strategy formulates an incomplete information, alternating-offers bargaining game on two variables, such as price per unit resource and percentage of bandwidth allocated, for both single and multiclass jobs at each node. We present a cost-optimal job allocation scheme for single-class jobs that involve communication delay and, hence, the link bandwidth. For fast and adaptive allocation of multiclass jobs, we describe three efficient heuristics and compare them under different network scenarios. The results show that the proposed algorithms are comparable to existing job allocation schemes in terms of the expected system response time over all jobs.

Quantum mechanics and molecular dynamic simulation provide important insights into structural configurations and molecular interaction data today. To extend this atomic/molecular level capability to system level understanding, we propose an "in silico" stochastic event based simulation technique. This simulation characterizes the time domain events as random variables represented by probabilities. This random variable is called the execution time and is different for different biological functions (e.g. the protein-ligand docking time). The simulation model requires fast computational speed and we need a simple transformation of the energy plane dynamics of the molecular behavior to the information plane. We use a variation of the collision theory model to get this transformation. The velocity distribution and energy threshold are the two parameters that capture the effects of the energy dynamics within the cell in our model. We use this technique to approximately determine the time required for the ligand-protein docking event. The model is parametric and uses the structural configurations of the ligands, proteins and the binding mechanism. The numerical results for the first moment show good correspondence with experimental results and demonstrate the efficacy of our model. The model is fast in computing and is less dependent on experimental data like rate constants

Random environment of the cell demands for a stochastic tool to analyze its behavior and bring the aspects of the bio-process that has been shadowed by the kinetic rate law based approach. In this work we present a novel random walk approach to detect the dynamics of passive diffusion of a metabolite in the gram-negative bacteria through phosphoenolpyruvate phospho-transfer system (pts pathway). We adopt a cell abstract model from the literature and build a triphase enzyme limited diffusion process on that. To explain the numerical results, we used the E.coli cell in our analysis to show the model precision. Our approach very finely manipulates the flux and flux responses coefficient with respect to enzyme variations in the cell. Also we have shown that current model would match the experimental in-vivo result better than kinetic rate base equivalent. Furthermore computational complexity of our approach is very light and could run in linear time

This paper proposes a new measurement architecture and associated traffic estimation algorithm called FastFlow that uses the heavy-tailed nature of Internet traffic in order to distinguish packets belonging to short lived flows (SLFs) and long lived flows (LLFs). While complete information is stored for SLFs, only partial information related to LLFs is collected using systematic sampling. The absence of data points in LLFs is approximated using a likelihood function defined over the coupon collector problem and the distribution of underlying traffic estimated using the non-parametric Parzen window technique. We validate the performance of our approach using traffic traces collected from our lab and observe that the estimated statistics match the observed traces with high accuracy.

The ever-growing demand for network capacity has resulted in the inception of optical burst switching (OBS) offering all-optical transmission, high-speed data rates and format transparent switching. But the current OBS architecture is very complex requiring costly fiber delay lines and quality of service management (QoS) techniques. In this paper we propose a new OBS architecture based on photonic container switching to be deployed in the core network. We show that our architecture will solve most of the complexities of existing OBS mechanisms, and in fact will make the core an all-optical, zero packet loss network that will also guarantee equal QoS to all the users. The packets are actually packed in fixed size containers which will be converted into an optical burst and transmitted through the network. Obviously a major issue to solve in our architecture is the scheduler design that ensures zero packet loss and no optical-to-electrical switching in the intermediate nodes. We devise a divide and conquer solution for the scheduler design problem and present some efficient algorithms for the same. We also analyze the performance of our algorithms under varying traffic conditions and network topologies, to ascertain their efficiency and robustness.

In this paper, we propose an adaptive forward error correction (FEC) and rate control technique to improve service quality in a wireless gaming environment. In particular, we concentrate on a centralized server gaming architecture (our results can be extended to peer-to-peer architectures as well), where wireless users can also connect to the gaming service. Our models are well-suited for last-hop wireless link users, but can also guarantee service improvement for other wireless scenarios through small modifications. It is assumed that the game server and clients (mobile devices) can switch between different prediction levels having different data rates. We introduce a new scheme for estimating the packet loss rates due to congestion and wireless channel conditions and use this information in a cross-layer design to improve the overall service quality. The congestion packet loss probability is used to devise a simple TCP-friendly rate control algorithm for sending downlink data packets from the game server. We also propose a novel adaptive FEC and dynamic packetization algorithm to alleviate the effects of wireless channel packet losses based on this chosen data rate. The simulation results show the efficacy of our scheme in achieving higher throughput.

In order to isolate malicious nodes in wireless sensor and actor networks and provide a secure routing, we formulate the attack-defense problem as a two-player, nonzero-sum, non-cooperative game between an attacker and a wireless sensor and actor network. We show that this game achieves Nash equilibrium and thus leads to a defense strategy for the network. We propose two novel schemes for preventing denial of service attack. The first approach is called utility based dynamic source routing (UDSR). It incorporates the total utility of each route in data packets, where utility is a value that we are trying to maximize in the game theoretic approach. The second approach is based on a watch-list, where each node earns a rating from its neighbors, based on its previous cooperation in the network. Results show that the proposed game frameworks significantly increase the chance of success in defense strategy for the wireless sensor and actor networks.

The design of the access networks of next generation broadband wireless systems requires special attention in the light of changing network characteristics. In this paper, we present a mesh-based distributed radio access network (RAN) framework for future wireless systems. Using short, high bandwidth optical wireless links to interconnect the various network elements, we identify a generic fractal or self similar structure in the network. A mathematical model for the framework is presented and the benefits of its scale-invariant properties on robustness, reliability and flexibility analyzed. We focus on three design parameters - carrier-class network reliability, network exposure due to failure conditions and system cost. The dynamics of these parameters on our proposed architecture are studied and compared against existing access network topologies like tree/ring and square-grid. The generality and recursive nature of our framework lends itself to be applied in interconnecting various heterogeneous broadband wireless access networks of the future

In this paper we have developed a new service classification strategy in hybrid scheduling scheme to support differentiated quality of service (QoS) among the different set of clients. The scheme dynamically computes the data access probabilities and amalgamates the push and pull scheduling schemes to develop the hybrid scheduling framework. While a flat scheduling is used for push system, the major novelty of the work lies in differentiating the clients based on their priority-classes and incorporating the effect of priority in selecting an item from the pull-system. Modeling and analysis of the system is performed to get an average behavior of the QoS parameters like delay in our hybrid scheduling framework. Simulation results points out that the average waiting time for the highest priority clients can be kept very low, while simultaneously minimizing the number of requests dropped by assigning appropriate fraction of available bandwidth. It also demonstrates that by intelligent selection of the cut-off point, used to segregate push and pull systems, the overall cost associated with the system can be minimized.

Wireless mesh based access networks are destined to play a pivotal role in next generation broadband systems. With the proliferation of mesh networks, a key issue for network designers is the design of an optimal mesh topology which minimizes cost while maintaining carrier-class features. In this paper, we formulate the design of an optimal mesh, taking network deployment cost, topological properties and carrier-grade reliability into account. Next, we present a genetic algorithm based algorithm (GaMa) for mesh topology design. We show that GaMa is capable of determining a generic mesh topology with carrier-class network features. The performance of the algorithm is compared with existing mesh topologies and gives improved results without the constraints of maintaining a regular topology.

This paper focuses on the assessment of the properties of security enforcement mechanisms for prevention of denial of service (DoS) attacks in wireless sensor networks. First part of the paper demonstrates the requirement for security enforcement using auction theory that allows detection of non cooperative nodes. In the proposed protocol, nodes prefer to participate in forwarding incoming packets and gaining reputation in the network. Nodes willing to do so must compete against each other. The competition is based on auction theory. We also formulate attack-defense problem as a non-cooperative nonzero-sum two-player game between an attacker and a wireless sensor network. This game achieves Nash equilibrium and thus leading to a defense strategy for the network. This approach is called utility based dynamic source routing (UDSR), which incorporates the total utility of each route in data packets. Results show that the proposed game frameworks significantly increase the chance of success in defense strategy for the wireless sensor network.

The essence of pervasive (ubiquitous) computing lies in the creation of smart environments saturated with computing and communication capabilities, yet gracefully integrated with human users. 'Context Awareness' is perhaps the most important feature of such an intelligent computing paradigm. The mobility and activity of the inhabitants play significant roles in forming the context at any instance of time. In order to extract the best performance and efficacy of smart computing environments, one needs a technology-independent, context-aware platform spanning over multiple inhabitants. In this paper, we have developed a framework for mobility-aware resource (in particular, energy consumption) management in a multi-inhabitant smart home, based on a dynamic, cooperative reinforcement learning technique. The inhabitants' mobility creates uncertainty of his location and activity. Using the proposed cooperative game-theory based framework, all the inhabitants currently present in the house attempt to minimize this overall uncertainty in the form of utility functions associated with them. Joint optimization of the utility function corresponds to the convergence to Nash equilibrium and helps in accurate prediction of inhabitants' future locations and activities. This results in adaptive control of automated devices and temperature of the house, thus providing an amicable environment and sufficient comfort to the inhabitants. Simulation results point out that our framework can adaptively control the smart environment, while reducing the energy consumption and enhancing the comfort.

In this paper we study the causal behavior of Rayleigh fading wireless channel and a single queue system buffer using the finite state Markov chain (FSMC) and the finite buffer fluid flow model. In the process, we propose a state partitioning scheme for capturing the wireless channel realities based on the combined effect of level crossing rate (LCR), average fade duration (AFD) and the average value of the signal SNR observed at the output of the matched filter or correlation demodulator. Relevant system parameters captured using such a scheme is linked with the fluid flow traffic model to create a modulated Markov process (MMP) that is used to calculate the packet loss rate and effective bandwidth of the system.

The ever-increasing popularity of Web services, growing demand for wireless multimedia and introduction of new, feature-enhanced, hand-held devices has already given birth to a new set of data-centric applications. Providing such applications with enhanced data processing capability calls for an efficient scheduling and transmission technique. The goal of most scheduling strategy lies in reducing the average waiting time. However, in most practical systems the variation of waiting time often results in client's impatience, thus provoking the clients to send repeated requests for the particular data item(s). In this paper we have developed a new hybrid scheduling framework for heterogeneous, asymmetric environments, by exploring the advantages of broadcasting very popular (push) data and dissemination of less popular (pull) data. The data access probabilities and the cut-off point used to segregate push and pull sets are dynamically computed. Packet fair scheduling (PFS) and stretch-optimal scheduling principle is deployed to obtain the push and pull schedule respectively. The framework explicitly takes care of the repeated requests originating from the impatient clients and minimizes the overall expected access time by obtaining an optimal cut-off point. Extensive performance analysis and simulation experiments are performed to show the efficiency of the system in reducing the overall expected access time (delay).

Flow and admission control algorithms have been proposed for efficient resource utilization in wireless networks with scarce and randomly varying resource availability. Transport and lower layer control protocols administer generic control behavior, ignoring particular application requirements or characteristics. Network-aware applications, on the other hand, enable us to develop application specific control mechanisms. We propose a novel control theory based adaptive resource management framework for network-aware scalable multimedia applications in wireless networks. In particular, we design an application-aware pro-active middleware based on level crossing analysis of stochastic models assisting a set of control algorithms founded on automatic control theory, thus avoiding network congestion and ensuring optimal resource utilization and application level QoS. Simulation experiments show that the resource management framework is capable of achieving bandwidth utilization within 1.5% of the optimum (theoretical) value and a delay jitter of 1.3 msec/sup 2/ only, for real-time video streaming. Also, it ensures a low session blocking rate (less than 10% for high session arrival rate) and high percentage of sessions with good quality video.

The competition among wireless data service providers brings in an option for the unsatisfied customers to switch their providers, which is called churning. The implementation of Wireless Local Number Portability (WLNP) is expected to further increase the churn rate (the probability of users switching the provider). However, the existing resource management algorithms for wireless networks fail to fully capture the far-reaching impact of this unforeseen competitiveness. From this perspective, we first formulate noncooperative games between the service providers and the users. A user's decision to leave or join a provider is based on a finite set of strategies. A service provider can also construct its game strategy set so as to maximize their utility (revenue) considering the churn rate. Based on the game theoretic framework, we propose an integrated admission and rate control (ARC) framework for CDMA-based wireless data networks. The admission control is at the session (macro) level while the rate control is at the link layer packet (micro) level. Two admission control modes are considered - one-by-one mode and batch processing mode, in which multiple users are admitted at a time. We show that: 1) for the one-by-one mode, the Nash equilibrium using pure strategy can be established for both under-loaded and fully-loaded systems and 2) for batch processing mode, there is either an equilibrium in pure strategy or a dominant strategy exists for the service provider. Therefore, the providers have clearly defined admission criteria as outcome of the game. Users are categorized into multiple classes and offered differentiated services based on the price they pay and the service degradation they can tolerate. We show that the proposed ARC framework significantly increases the provider's revenue and also successfully offers differentiated QoS to the users.

For next generation wireless cellular networks, the radio access network (RAN) component is destined to evolve into a high-capacity, flexible and reconfigurable network architecture supporting smaller cell sites and newer technologies. Based on the well-known Petersen graph, in this paper we propose a RAN architecture, named PeterNet, that interconnects the network elements in a mesh topology. Focusing on optical wireless as the underlying transmission technology, we analyze our architecture on two key indices - carrier-class network reliability (99.999%) and infrastructure cost - providing comparative performance analysis with existing tree/star and regular grid networks. Furthermore, we generalize our architecture to what we call, the GPeterNet, which allows dynamic reconfiguration and redesign of the access network while leveraging the underlying salient features.

Based on cooperative game theory, we propose a new technique for handling security issues in mobile wireless sensor networks. We define a game between sensor nodes and concentrate on three fundamental factors: cooperation, reputation and quality of security. Stronger cooperation between two nodes implies more reliable data communication between them. And the more a node cooperates the better is its reputation, which decreases when misbehavior is detected. When security of the network is compromised, the percentage of exposed traffic measures the quality of security of sensor nodes. By incorporating these three factors, we cluster the sensor nodes such that within a cluster, the payoff function of all sensor nodes are close to each other, where payoff is the largest possible individual gain for each sensor according to a defined utility metric. We define one strategy set for each node, which guarantees reaching to an equilibrium point for payoff function.

Summary form only given. This article realizes the vision of mobile grid computing by proposing a fair pricing strategy and an optimal, static job allocation scheme. Mobile devices has not yet been integrated into grid computing platforms mainly due to their inherent limitations in processing and storage capacity, power and bandwidth shortages. However, millions of laptops, PDAs and other mobile devices remain unused most of the time and this huge resource repository can be potentially utilized in the grid environment. Here, we propose a game theoretic pricing model, to address load balancing issues in mobile grids. In particular, by drawing upon the Nash bargaining solution (NBS), we show that we can obtain an unified framework for addressing such issues as network efficiency, fairness, utility maximization, and pricing. The advantage of this framework is that we have a precise mathematical characterization of the solutions and their properties. Our current endeavor characterizes a two-player alternating-offer bargaining game between the wireless access point (WAP) server and the mobile devices to determine the pricing strategy. This pricing strategy is then made use of to effectively distribute jobs to the mobile devices. Our job allocation scheme maximizes the revenue of the grid user, and yet is comparable to the overall system response time of other load balancing schemes.

Summary form only given. A hybrid scheduling is introduced that effectively combines broadcasting of more popular data (push data) and dissemination upon-request for less popular data (pull data), for asymmetric environments where the clients outnumber the servers having higher downlink communication (server to client) bandwidth than the uplink communication (client to server) bandwidth. We do not assume prior knowledge of the data access probability; in fact data access probabilities and thereby the cut-off-point to separate the push and the pull set are computed dynamically. In our scheme all the data items are assumed to be of variable length arranged in descending order of their access probabilities. The clients send their requests to the server, which queues them up for the pull items. At any instant of time, the item to be broadcast is designated applying a pure-push scheduling; whereas the item to be pulled is the one stored in the pull-queue, which has accumulated, so far, the highest number of pending requests with minimum service time requirement. The expected waiting time spent by a client in the hybrid schedule is evaluated analytically, and the cut-off point between push and pull items is chosen to minimize waiting time.

A completely visible pervasive transaction environment where it is possible to link all related distributions of physical objects and trace their mobility through their entire life process, has been elusive. With the emergence of radio frequency identification (RFID) based object tags, it is now practicable to automatically collect information pertaining to the object's place, time, transaction, etc. We propose an architecture for pervasive real-time tracking of object distribution and subsequently present an efficient mechanism for performing recall of RFID tagged objects that were previously distributed but turned out defective. Applying the concepts of scale free networks and epidemic theory, we mathematically model the distribution and recall process and get a stochastic estimate of the average spread of object distributions and the number of recall messages required. Our simulation results validate the analysis and the small average number of recall messages obtained proves the efficacy of the scheme.

A completely visible pervasive transaction environment where it is possible to link all related transactions of physical objects and trace their mobility through their entire life process, has been elusive. With the emergence of radio frequency identification (RFID) based tags, it is now practicable to automatically collect information pertaining to any object's place, time, transaction, etc. Based on the pervasive deployment of RFID tags, we propose A novel ubiquitous architecture followed by a protocol for tracking mobile objects in real-time. Our delay analysis and simulation results indicate that the delay incurred in the database update of current tag location is very low and is in the order of seconds, thus providing a very fine granularity in time for consistent location update requests.

Insufficiency of memory and battery power of sensors makes the security of sensor networks a hard task to do. This insufficiency also makes applying the existing methods of securing other type of networks on the sensor networks unsuitable. We propose a game theoretic framework for defensing nodes in a sensor network. We apply three different schemes for defense. Our main concern in all three schemes is finding the most vulnerable node in a sensor network and protecting it. In the first scheme we formulate attack-defense problem as a two-player, nonzero-sum, non-cooperative game between an attacker and a sensor network. We show that this game achieves Nash equilibrium and thus leading to a defense strategy for the network. In the second scheme we use Markov decision process to predict the most vulnerable sensor node. In the third scheme we use an intuitive metric (node's traffic) and protect the node with the highest value of this metric. We evaluate the performance of each of these three schemes, and show that the proposed game framework significantly increases the chance of success in defense strategy for sensor network.

Since the routing is the most energy-consuming operation in large wireless sensor networks, the routing mechanisms need to dynamically distribute the routing load to multiple sensors in order to maximize the number of live sensors during a given time unit. In this paper we propose a novel angle-based dynamic path construction (ADPC) scheme for routing load distribution with a goal of ultimately extending the network lifetime. The ADPC scheme dynamically constructs a routing path to the base station with the help of a set of routers extracted from local neighbors. The router set selection is based on an angle, called routing angle, which plays a key role in controlling the number of routers and the length of the routing path which influences the data delivery latency. Each such router is chosen as a next-hop based on its current routing service load, thus achieving the delay-aware and energy-conserving routing load distribution. Simulation experiments demonstrate that the ADPC scheme leads to a much lower rate of sensor failures and is able to control the data delivery latency as compared to a single (alternate) path routing scheme.

In this paper, we provide a game theoretic approach for maximizing the utility of a carrier in a competitive market. Due to the deregulation of the telecommunications industry there is more than one service provider in any region. This gives the users the flexibility to switch their provider if they are not satisfied with their service. In this perspective, we propose a utility function based on non-cooperative game which considers the probabilities of users leaving the network. We categorize users into three classes who get differentiated services based on the price they are willing to pay. The game theoretic approach allocates resources both during service admission and burst admission. The utility function considered is from the service provider's point of view. Our model demonstrates the impact of admitting high paying users on other users.

The competition among wireless data service providers brings in an option for the customers to switch their providers, due to unsatisfactory service or otherwise. However, the existing resource management algorithms for wireless networks fail to fully capture the far-reaching impact of this competitiveness. From this perspective, we propose an integrated admission and rate control (ARC) framework for CDMA based wireless data networks. The admission control is at the session (macro) level while the rate control is at the link layer packet (micro) level. The ARC framework is based on a novel game theoretic formulation which defines non-cooperative games between the service providers and the customers. A user's decision to leave or join a provider is based on a finite set of strategies. A service provider can also construct its game strategy set so as to maximize the utility (revenue) yet attaining its target churn rate (the probability of users leaving the network). We show that the pure strategy Nash equilibrium can be established for both under-loaded and fully-loaded systems such that the providers have clearly defined admission criteria as outcome from this game. Users are categorized into multiple classes and offered differentiated services based on the price they pay and the service degradation they can tolerate. We show that the proposed ARC framework significantly increases the provider's revenue and also successfully offers differentiated QoS to the users.

In recent years, wide bandwidth and low cost wireless LAN (WLAN) technology has emerged as a competitive choice for high speed wireless Internet access. To support the Internet mobility for the frequently moving mobile nodes in the local WLAN environment, Mobile IP has been found to be inefficient due to its high location update and packet delivery cost. This paper proposes an alternative architecture for network-layer mobility support using dynamic client configuration and transparent proxy mechanism. The attractive feature of our solution is that it requires no change in the legacy network infrastructure. We have implemented a prototype of the proposed architecture, and have taken experimental measurements to evaluate its performance. Experimental results show that the proposed architecture is capable of supporting IP mobility with the handoff delay less than a second. In addition, we have done an analytical study to test the scalability of the proposed architecture. Results show that performance of the architecture is not severely affected by the user mobility and a commonplace router is capable of supporting a considerable number of such users.

The rapid advances in a wide range of wireless access technologies along with the efficient use of smart spaces have already set the stage for the development of smart homes. Context-awareness is perhaps the most salient feature in these intelligent computing platforms. The "location" information of the users plays a vital role in defining this context. To extract the best performance and efficacy of such smart computing environments, one needs a scalable, technology-independent location service. We have developed a predictive framework for location-aware resource optimization in smart homes. The underlying compression mechanism helps in efficient learning of an inhabitant's movement (location) profiles in the symbolic domain. The concept of Asymptotic Equipartition Property (AEP) in information theory helps to predict the inhabitant's future location as well as most likely path-segments with good accuracy. Successful prediction helps in pro-active resource management and on-demand operations of automated devices along the inhabitant's future paths and locations - thus providing the necessary comfort at a near-optimal cost. Simulation results on a typical smart home floor plans corroborate this high prediction success and demonstrate sufficient reduction in daily energy-consumption, manual operations and time spent by the inhabitant which are considered as a fair measure of his/her comfort.

The next-generation wireless networks need to support a wide range of multimedia applications with limited radio resources like bandwidth. In this paper, we propose a novel integrated framework for bandwidth degradation and call admission control (CAC) for multiclass real-time multimedia traffic in such networks. To increase the total carried traffic in an overloaded (saturated) wireless system, some of the ongoing calls in our framework are allowed to operate under a degraded mode, thereby releasing wireless channels that can be used to accommodate new calls, however, at the cost of user satisfaction. Indeed, an increase in carried traffic (i.e., provider's revenue generation) and user's quality-of-service satisfaction are two conflicting goals in a bandwidth allocation scheme. The proposed framework adequately models this tradeoff by introducing the negative revenue (i.e., loss) from bandwidth degradation, and finding the optimal degradation and admission policies that maximize the net revenue. When there is a mixture of real-time and nonreal-time calls in the system, the former are given preemptive priority over the latter, which are buffered for future admission in case of preemption. A channel sharing scheme is proposed for nonreal-time traffic and analyzed using a Markov modulated Poisson process-based queueing model. Detailed simulation experiments are conducted to validate our proposed framework.

Intelligent mobile terminals (or users) of next generation wireless networks are expected to initiate voice over IP (VoIP) calls using session set-up protocols like H.323 or SIP (session initiation protocol). To guarantee the service quality of such applications, the call set-up protocol should be robust against network impairments. We analyze the performance of the H.323 call set-up procedure over wireless links using a simple call model under two modes of operations, namely, regular and fast connect. The proposed model assumes the presence of a radio link protocol (RLP) and recommends that the VoIP packets be transferred without any RLP retransmissions, while H.323 control packets be transferred with RLP retransmissions. Our analytical models and detailed experiments show that the VoIP call set-up performance can undergo significant degradation if RLP is not used at all, even for moderately high frame error rates (FERs) in wireless links. On the other hand, a robust radio link layer, such as RLP, can improve the call-set-up delay performance as compared to the existing wireless voice call-set-up delay.

In a telecommunication network, when a new network element is installed into the network, the new network element has to take the responsibility to fit itself into the network by forcing the changes in the existing network elements through the configuration processes. This paper describes an approach that allows the new network element being accepted by the existing network through auto-configuration and topology management functions. This makes the configuration management process of the telecommunication network simple, less expensive and less error prone.

The explosive growth in wireless networks and the Internet creates considerable demand on wireless carriers to provide wireless Internet services. There are many challenges to overcome in order to realize true wireless Internet service solution. This paper reviews those challenges in wireless networks from mobility perspective and identifies important areas that have to be resolved to create a framework for universal mobility in wireless Internet.

Internet services continue to show a remarkable sustained growth; this is complemented with an increased demand in mobility support over wide areas. The cellular systems have a widespread infrastructure that can be used to provide data services. In particular, CDPD (cellular digital packet data) is a technology that provides reliable data transmission over the AMPS (advanced mobile phone system) cellular network, without upsetting voice services. Among the demanded services there are file transfers, send/receive electronic mails (E-mail) and the WWW (hypertext browser service) that has turned out to be the most popular service. This paper presents an analysis methodology, under multiple channels, of the total capacity for CDPD use. Emphasis is paid to Internet services because this is the most stringent case, both in terms of transmission capacity and message delay. Results show that multiple channels improve the CDPD performance in terms of the quality of service and users supported.

The current wireless networks will not be able to cope with the expected growth in data and multimedia services in a flexible and cost-effective manner. This paper presents the wireless multimedia service opportunities. It includes a discussion on wireless multimedia services and their characterization. A practical model is given to estimate the diffusion of wireless multimedia services in the network. It discusses the benefits of using IP centric solutions for wireless, and the challenge of QoS and wireless mobility to make this IP centric solution realizable. It proposes network and service architecture solutions that combine the current wireless access standards into the core IP network. It also shows how an IP addressable terminal can be connected to this IP wireless network to make the multimedia service implementation simpler. If a convergence of the mobile and Internet technologies can be achieved, it would be a powerful force in realizing vast economies of scale and enabling a wireless lifestyle.

Each wireless communication system has its own unique operating conditions. RF conditions, call traffic, and subscriber mobility of every sector are different from others. In order to achieve maximum capacity and optimal performance of a network, it is crucial to have an efficient channel assignment method that dynamically fits to the unique operating conditions of the network. In this paper, a self-engineered adaptive channel allocation (SEACA) scheme is proposed. The SEACA employs a self engineering engine that monitors network operating condition changes which include RF conditions, call traffic, subscriber mobility, and network resource utilization, then it decides an optimal time to adjusts channel assignment of each cell. SEACA provides the most feasible and effective adaptive channel assignment scheme in today's networks by de-coupling the channel allocation process from real-time call processing which has been a major limitation of typical dynamic channel allocation and adaptive channel allocation.

The wireless access is expected to be one of the key access technologies for providing IP services to the user, end-to-end seamlessly. The wireless network, as the "last hop" of the wireline IP network has its own unique set of complex characteristics. To improve the behavior of the wireless link susceptible to frequent error bursts (due to fading, shadowing etc.), various low layer (physical/link layer) techniques have to be used to map the service associated network level QoS parameters such as delay, jitter, BER and throughput to meet end-to-end IP performance. The motivation of this paper is two-fold: (i) to present some of the unique characteristics of the radio link and show what kind of flexibility of resource management and mapping techniques required to guarantee QoS over the wireless, and (ii) propose a framework for a wireless QoS agent. The wireless QoS agent, in a nutshell, will be responsible for mapping multimedia IP QoS requirements to radio link specific requirements. The wireless QoS agent will interwork with the IP QoS Manager framework within IETF such as diff-serv in core networks.

Article Free Access Share on TCP source activity and its impact on call admission control in CDMA voice/data network Authors: Sanjoy Sen. Jastinder Jawanda Sortel Wireless Networks, 2201 Lakeside Boulevard, Richardson, TX Sortel Wireless Networks, 2201 Lakeside Boulevard, Richardson, TXView Profile , Kalyan Basu Sortel Wireless Networks, 2201 Lakeside Boulevard, Richardson, TX Sortel Wireless Networks, 2201 Lakeside Boulevard, Richardson, TXView Profile , Naveen K. Kakani Center for Research in Wireless Computing (CReW), Department of Computer Science, University of North Texas, Denton, TX Center for Research in Wireless Computing (CReW), Department of Computer Science, University of North Texas, Denton, TXView Profile , Sajal K. Das Center for Research in Wireless Computing (CReW), Department of Computer Science, University of North Texas, Denton, TX Center for Research in Wireless Computing (CReW), Department of Computer Science, University of North Texas, Denton, TXView Profile Authors Info & Claims MobiCom '98: Proceedings of the 4th annual ACM/IEEE international conference on Mobile computing and networkingOctober 1998 Pages 276–283https://doi.org/10.1145/288235.288323Published:25 October 1998Publication History 4citation356DownloadsMetricsTotal Citations4Total Downloads356Last 12 Months6Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF