1,721,069 research outputs found
Pricing for Past Channel State Information in Multi-Channel Cognitive Radio Networks
No full textCognitive Radio (CR) networks have received significant attention as a promising approach to improve the spectrum efficiency of current license-based regulatory system. In CR networks, a Secondary User (SU) can use a spectrum vacancy that can be detected by either sensing-before-transmission or database access. However, it is often difficult to detect a vacant spectrum opportunity because of inaccuracies due to sensing and delays to update and/or the database that holds this information. In this paper, we develop a hybrid detection framework in multi-channel CR networks, where an SU can selectively sense a channel for spectrum vacancy by accessing the spectrum history of Markovian channels. We focus on the value of the channel history information offered by the Primary Provider (PP) of each channel, and consider a market for the information exchange between multiple PPs and SUs. We investigate the interplay between of the PPs and the SUs through their pricing and buying decisions for this information, in the presence of sensing inaccuracy, i.e., false alarm and miss detection
Distributed CSMA Algorithms for Link Scheduling in Multihop MIMO Networks Under SINR Model
Get PDFabstract: In this paper, we study distributed scheduling in multihop multiple-input-multiple-output (MIMO) networks. We first develop a "MIMO-pipe" model that provides the upper layers a set of rates and signal-to-interference-plus-noise ratio (SINR) requirements that capture the rate-reliability tradeoff in MIMO communications. The main thrust of this paper is then dedicated to developing distributed carrier sense multiple access (CSMA) algorithms for MIMO-pipe scheduling under the SINR interference model. We choose the SINR model over the extensively studied protocol-based interference models because it more naturally captures the impact of interference in wireless networks. The coupling among the links caused by the interference under the SINR model makes the problem of devising distributed scheduling algorithms very challenging. To that end, we explore the CSMA algorithms for MIMO-pipe scheduling from two perspectives. We start with an idealized continuous-time CSMA network, where control messages can be exchanged in a collision-freemanner, and devise a CSMA-based link scheduling algorithm that can achieve throughput optimality under the SINR model. Next, we consider a discrete-time CSMA network, where the message exchanges suffer from collisions. For this more challenging case, we develop a "conservative" scheduling algorithm by imposing a more stringent SINR constraint on the MIMO-pipe model. We show that the proposed conservative scheduling achieves an efficiency ratio bounded from below.This is the authors' final accepted manuscript. The published version can be accessed at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6256765.
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Analytical characterization of internet security attacks
No full textInternet security attacks have drawn significant attention due to their enormously adverse impact. These attacks includes Malware (Viruses, Worms, Trojan Horse), Denial of Service, Packet Sniffer, and Password Attacks. There is an increasing need to provide adequate defense mechanisms against these attacks. My thesis proposal deals with analytical aspects of the Internet security attacks, as well as practical solutions based on our analysis. First, We focus on modeling and containment of internet worms. We present a branching process model for the propagation of worms. Our model leads to the development of automatic worm containment strategies, which effectively contain both uniform scanning worms and local preference scanning worms. Incremental deployment of our scheme provides worm containment for local networks when combined with traditional firewalls. Next, we study the capacity of Bounded Service Timing Channels. We derive an upper bound and two lower bounds on the capacity of such timing channels. We show that when the length of the support interval is small, the uniform BSTC has the smallest capacity among all BSTCs. Based on our analysis, we design and implement a covert timing channel over TCP/IP networks. We are able to quantify the achievable data rate (or leak rate) of such a covert channel. Moreover, by sacrificing data rate, we are able to mimic normal traffic patterns, which makes detecting such communication virtually impossible
Statistical multiplexing of regulated flows in networks: Some structural properties and a framework for end-to-end performance analysis
No full textAn important, yet challenging, issue in the traffic engineering of high-speed networks is to determine the statistical performance when bursty traffic are multiplexed. Important performance metrics are the end-to-end delay and packet loss characteristics. The key to resolving the performance is the buffer occupancy distribution at the nodes. While this is fairly well understood in single buffers, the end-to-end problem is largely unsolved in the statistical context. A useful heuristic is the so-called Negligible Jitter conjecture that states that the end-to-end performance is bounded by the performance in a network assuming Better than Poisson (BTP) traffic at each node and then using the standard M/G/1 analysis with independence assumptions. The crucial question that arises is whether the BTP assumption is realistic and the applicability is broad. This dissertation is devoted to this important issue and to develop a framework for analyzing the end-to-end statistical performance for flows regulated by leaky bucket regulators as in real networks. We consider the problem for networks with FIFO scheduling and independent input streams at the network ingress. We show that the BTP holds for regulated sources and obtain explicit and accurate estimates for the tail and mean distributions of the workload. Furthermore, we study the burstiness behavior of regulated traffic inside the network. We show that a single flow inherits its initial bursty properties with a distribution converging to the burst size it initially obtains at the network access provided its contribution is small with respect to the aggregate. We also obtain explicit models for the burstiness of aggregate flows. These results lead to explicit bounds for the end-to-end mean delay performance. All these performance bounds give insights for network QoS provisioning and designing admission control strategy. Finally we consider concentrator networks as a special, but important, case. We show that the workload increases in distribution when their input flows are replaced by the original independent traffic streams. This result gives a very simple but effective approach to estimate the statistical performance of such networks. The ash exhibited a high acid neutralizing capacity that increased with retention time, and neutralization of ground and surface water was observed at the site. However, pore-water within the ash fill contained potentially hazardous constituents, most of which were depleted slowly from ash and reached higher aqueous concentrations at extended retention times. The two main constituents of concern were arsenic and boron. Arsenic transport was highly attenuated by soil with As(III) being more mobile than As(V). Arsenic has not been detected in downgradient monitoring wells and its transport is highly dependent on preferential flow conditions. Boron exhibited low sorption to soil and its transport lagged slightly behind groundwater flow. Thus, release of boron from ash and groundwater flow rate control its mobility. A fraction of the boron in ash was solubilized immediately upon water contact and other fractions were released more slowly, consistent with boron partitioning during combustion. Over 50% of the total boron was released slowly indicating that ash may be a long-term source. For both elements, groundwater flow rates, preferential flow, and dilution are critical in evaluating environmental impacts. Assuming no preferential flow, boron and arsenic require over 100 and 30,000 years to reach a downgradient creek which is utilized by wildlife. A creek flow rate of at least 1.6 L/s, which is reasonable, would dilute both elements to acceptable levels
CAS: Context-Aware Background Application Scheduling in Interactive Mobile Systems
No full textEach individual's usage behavior on mobile devices depends on a variety of factors, such as time, location, and previous actions. Hence, context-awareness provides great opportunities to make the networking and computing capabilities of mobile systems more personalized and more efficient in managing their resources. To this end, we first reveal new findings from our own Android user experiment: 1) the launching probabilities of applications follow Zipf's law and 2) inter-running and running times of applications conform to log-normal distributions. We also find contextual dependencies between application usage patterns, for which we classify contexts autonomously with unsupervised learning methods. Using the knowledge acquired, we develop a context-aware application scheduling framework, context-aware application scheduler (CAS), that adaptively unloads and pre-loads background applications for a joint optimization in which the energy saving is maximized and the user discomfort from the scheduling is minimized. Our trace-driven simulations with 96 user traces demonstrate that the context-aware design of the CAS enables it to outperform existing process scheduling algorithms. Our implementation of the CAS over Android platforms and its end-to-end evaluations verify that its human-involved design indeed provides substantial user-experience gains in both energy and application launching latenc
Stratified best -effort QoS provisioning in noncooperative networks
No full textProviding quality of service (QoS) to a diverse user base with heterogeneous service requirements is crucial to the success of the next generation Internet. The stratified best-effort service (SBS) architecture is proposed for this purpose. The primary goal is to provide graded services with per-flow QoS using service classes in routers without per-flow state. In the context of Diffserv, SBS provides soft, quantitative service specifications using certain PHB groups. QoS is induced as the result of the interaction of selfish users sharing common network resources, or noncooperative self-provisioning. Pricing schemes are essential to this architecture. Users will act selfishly but higher price prevents all users from rushing into the best service. So between users and networks, the edge-routers will charge higher price for packets requiring better QoS. First, a model is presented for multi-class QoS provisioning. The theoretical analysis of noncooperative multi-class QoS provisioning games in the single switch case includes existence criteria for Nash equilibria and conditions under which they are Pareto and/or system optimal. Second, we present and study a specific network architecture for facilitating noncooperative QoS provisioning in many switch systems with emphasis on realizability. The noncooperative many switch QoS provisioning problem is reduced to a distributed control problem. We present simulation results which show that our architecture is able to provide stable, stratified services to traffic with diverse QoS requirements. Lastly, we study the ordering properties of QoS measures in multi-class QoS provisioning systems when generalized processor sharing (GPS)-based packet scheduling is employed in routers
Routing for multi -hop wireless networks
No full textOver the last few years, multi-hop wireless networks have received considerable attention. Routing is an important functionality for such networks as it is closely tied to energy efficiency, scalability, and performance. Unlike wired networks, in wireless systems due to the nature of the communication environment, issues such as mutual interference and errors need to be accounted for in the overall design. In Part I, we develop an energy-efficient routing algorithm that considers intrinsic wireless network characteristics to maximize network performance. To that end, we explicitly study the impact of interference on the network, and combine three key wireless metrics: transmission power; interference ; and residual energy. The proposed algorithm is designed to accommodate any combination of these key elements and to automatically detour around congested areas, which helps improve overall network performance. Using simulations, we show that the routes chosen by our algorithm (centralized and distributed) are more energy efficient than the-state-of-the-art. In Part II, we study geographic information issues on routing for multi-hop wireless networks: routing algorithm design and performance analysis. Due to the simplicity and scalability, routing algorithms using geographic information (geographic routing) have been proposed. However, in practice location errors could significant degrade routing performance. In the mobile environment, the performance degradation becomes even more severe. Hence, we study the impact of location errors on geographic routing algorithms and propose a routing algorithm to mitigate the impact of location errors. Geographic and geometric attributes affect network performance. We use geometric probability to analyze the nodal load, which is defined as the number of packets served at a node, induced by straight line routing in large homogeneous multi-hop wireless networks. Our analysis shows that the nodal load at each node is a function of the node\u27s Voronoi cell, the node\u27s location in the network, and the traffic pattern specified by the source and destination randomness and straight line routing. Since load distribution depends on the traffic pattern generated by straight line routing, contrary to conventional wisdom, straight line routing can balance the load over the network, depending on the traffic patterns
Simplification of Network Dynamics in Large Systems
No full textControlling today\u27s communication networks is a challenging task due to the tremendous growth both in terms of the network capacity and in the number of elements (e.g., end-users, routers and hosts) that the network supports. As the size of the network grows, the network dynamics also become increasingly complex. Solutions that once work well for small networks may no longer be appropriate for large-scale and high-bandwidth networks. In this dissertation, we have taken two orthogonal approaches to simplify the network dynamics in large communication systems. In the first approach, we seek simplicity through exploiting the largeness of the network. We first study the pricing-based control problem and the Quality-of-Service routing problem in large-capacity wire-line networks. We show that simple static control policies can approach the performance of the optimal (but complex) dynamic control policy when the capacity of the system is large. We develop simple and distributed control algorithms based on these static control policies. Our control solution can significantly reduce the computation complexity and communication overhead without sacrificing the network performance. We then turn to wireless networks and investigate the fundamental tradeoff between the capacity and the delay in large mobile wireless networks. By exploiting the largeness in the number of nodes in these networks, we obtain simple scaling laws that determine the optimal achievable capacity given delay constraints. In the second approach, we seek simplicity by designing an appropriate control architecture such that complex interactions within the system can be structured into layers that are only weakly dependent on each other through a judiciously chosen set of control parameters. In particular, we investigate the cross-layer congestion control and scheduling problem in multi-hop wireless networks. We develop a loose-coupling approach to this problem, where the cross-layer solution only requires a minimal amount of interaction between the layers, and is robust to imperfect decisions at each layer. This result allows us to use imperfect, but simpler and potentially distributed, algorithms for cross-layer control of large wireless networks. We have successfully developed such a fully distributed cross-layer control solution for certain interference model
Distributed flow control for next generation networks
No full textIn this work, we investigate the flow control problem for the next generation Internet. The flow control problem involves determining the rates at which traffic flows from various sources should be transmitted over the network. Providing efficient and distributed flow control mechanisms is very important in maximizing network throughput as well as minimizing network delays. Flow control is inherently difficult because we expect that networks will continue to become even larger and more complex (hence scalability becomes critical) and will need to support a variety of different applications with diverse performance requirements (all traffic may not even be controllable). For example; the network may send explicit data rate information to the source or may send simple binary-bit indications of the network status to the source. While the explicit-rate flow control model is widely used for theoretical analysis, in practice, it is the binary-bit scheme that has been widely deployed. One example of the binary-bit flow control is the famous Additive Increase Multiplicative Decrease (AIMD) that has been used in the most dominant protocol of the current Internet, TCP. In our work, we develop our theoretical results assuming an explicit-rate flow control model and then based on this analysis provide practical AIMD type of solutions for Internet. Unlike other works in the literature, we consider a network with both controllable and uncontrollable flows. We begin by analyzing a network with a single bottleneck link and then extend the analysis to a general network with multiple links. In contrast to other works, we focus on the queueing delays caused by the controller and provide guidelines on how to design an efficient flow control system based on rigorous queueing theoretic results. We believe that the queueing behavior is very important because it determines network performance. In fact the main objectives of flow control, i.e., high utilization, low loss rate, and fairness are all related to the queueing behavior within the network. Based on our theoretical results, we provide efficient distributed flow control mechanisms that can be implemented in the TCP context using Active Queue Management (AQM) schemes. We further analyze an AIMD network using general AQM schemes when the number of flows in the network is large. The purpose of this work is to clearly understand how AIMD can affect the queueing behavior within a network, and whether different AQM schemes can result in widely differing network performance
Traffic management and control in ATM networks
No full textHigh-speed ATM networks are expected to support various types of applications, each with their own Quality of Service (QoS) requirements. Each application may generate one or more classes of traffic such as voice, video, still images, and data. The problem of utilizing the network efficiently and not (statistically) violating the negotiated QoS requirements of existing applications has been the subject of extensive research. In this thesis we study aspects of this problem that involve scheduling and flow control. We characterize the different traffic classes into two main types: real-time and controlled traffic. The real-time traffic consists of applications with stringent delay and loss constraints such as video and voice traffic. The controlled traffic, composed mainly of current Internet data traffic, can tolerate large delays but requires lossless transmission. We propose an effective hop-by-hop feedback flow control framework to support these types of traffic classes and maintain high network utilization. The proposed flow control mechanism provides lossless service for the controlled traffic. To guarantee QoS requirements for the real-time traffic, we develop optimal scheduling algorithms based on different delay and priority constraints of the traffic. We define and investigate the complexity of real-time scheduling algorithms, then develop simpler heuristic scheduling algorithms based on our optimal algorithms. We use an analytical model to estimate the loss rate performance and gain insight on the need for scheduling and when it is most beneficial. Finally, we present some concluding remarks on how this research might be extended in different directions
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