A simulation study of block management in BitTorrent

Among the existing P2P systems for content distribution, BitTorrent (BT) is the most popular one which has attracted keen attentions from both industrial and academic forces in recent years. Its superior performance is due to the multipart downloading scheme by dividing the large file into thousands of small blocks to enable the cooperative down-loading among participants. Since transmissions are provoked by interested blocks only, the block distribution will seriously affects the performance of the system, i.e., robustness and throughput. As a result, how to manage the circulation of blocks is important both theoretically and practically. BT leverages on the Local Rarest First scheme to pursue the even distribution of blocks to help peers locate what they need easily. Surprisingly, how good is its performance with heterogenous networks has never received research attention before and this motivates our work. In this study, we carried out simulations to investigate the evolution of block distribution in BT. We find that the block distribution is far from optimal in terms of block frequency (with some blocks dominating the network and some becoming extinct nearly) and topology (with same blocks tending to conglomerate). We also propose a simple source coding mechanism to achieve a BT like network with much improved performance in this view. © 2006 ACM

Efficient spectrum sharing and power control in cognitive radio networks

Cognitive radio technology solves the spectrum under utilization problem by enabling the secondary users access the spectrum holes opportunistically. In this paper, we are interested in how to share the spectrum holes among the secondary users, with the objective of maximizing the total spectrum utilization. We present a cross-layer design including spectrum sharing and power control. Spectrum sharing determines which neighbor a node will communicate with and which channel this communication will take place; power control decides which power level a node will use. We propose a Binary Integer Linear Programming (BILP) formulation, and use LINGO to find the optimal solution. With the assumption that all nodes transmit at a same power level, we find that there exists an optimal common power level at which the total spectrum utilization is maximized. Numerical results demonstrate that, using the optimal common power level not only improves the total spectrum utilization, but also reduces the complexity of the BILP problem. Copyright 2007 ACM

Effective bandwidth utilization in IEEE 802.11e

IEEE 802.11e standard develops a reference design for a sample scheduler and admission control unit to support the contention-free access. However, the reference design can not effectively utilize the bandwidth. This paper proposes an equal-spacing-based (equal-SP) design to address the problem. In the equal-SP design, which generalizes the reference design, each stream is scheduled with equal-spacing and different streams are scheduled with different equal-spacings. The equal-SP design not only keeps all advantages of the reference design, but it can also utilize the bandwidth effectively. Copyright 2007 ACM

Joint design of spectrum sharing and routing with channel heterogeneity in cognitive radio networks

Cognitive radio technology solves the spectrum under-utilization problem by enabling the secondary users access the spectrum holes opportunistically. Therefore, how to efficiently share the spectrum holes among the secondary users is of interest. Previous studies on spectrum sharing focused on the formulations with homogeneous channels. The channel heterogeneity, which is a unique feature in cognitive radio networks, has been ignored. In this paper, we model the channel heterogeneity and present a cross-layer optimization framework which jointly considers the spectrum sharing and routing with the objective of maximizing the fairness ratio. Since the formulation is in the forms of mixed integer linear programming (MILP), which is generally a difficult problem, we develop a heuristic method by solving a relaxation of the original problem, followed by rounding and simple local optimization. Simulation results show that the heuristic approach performs very well, i.e., the solutions obtained by the heuristic approach are very close to the global optimum obtained via LINGO. To the best of our knowledge this is the first attempt to model the channel heterogeneity into the formulation of spectrum sharing in cognitive radio networks. © 2009

Distributed power allocation algorithm for spectrum sharing cognitive radio networks with QoS guarantee

In this paper we study the distributed multi-channel power allocation for spectrum sharing cognitive radio networks with QoS guarantee. We formulate this problem as a non-cooperative game G_MCPA-C with coupled strategy space to address both the co-channel interference among secondary users and the interference temperature regulation imposed by primary systems. We investigate the properties of Nash equilibrium (N.E.) for our G_MCPA-C, including the existence and QoS provisioning. Furthermore, we derive a layered structure by applying the Lagrangian dual decomposition to G_MCPA-C and design a distributed algorithm to find the N.E. via this structure. Simulation results are presented to show both the validity of our game theoretic model and the performance of our proposed algorithm. Finally, we incorporate the Pigouvian taxation into our algorithm to improve the efficiency of N.E. when social optimality is considered. © 2009 IEEE

Cross-layer throughput optimization in cognitive radio networks with SINR constraints

Recently, there have been some research works in the design of cross-layer protocols for cognitive radio (CR) networks, where the Protocol Model is used to model the radio interference. In this paper we consider a multihop multi-channel CR network. We use a more realistic Signal-to-Interference-plus- Noise Ratio (SINR) model for radio interference and study the following cross-layer throughput optimization problem: (1) Given a set of secondary users with random but fixed location, and a set of traffic flows, what is the max-min achievable throughput? (2) To achieve the optimum, how to choose the set of active links, how to assign the channels to each active link, and how to route the flows? To the end, we present a formal mathematical formulation with the objective of maximizing the minimum end-to-end flow throughput. Since the formulation is in the forms of mixed integer nonlinear programming (MINLP), which is generally a hard problem, we develop a heuristic method by solving a relaxation of the original problem, followed by rounding and simple local optimization. Simulation results show that the heuristic approach performs very well, that is, the solutions obtained by the heuristic are very close to the global optimum obtained via LINGO. © 2010 M. Ma and D. H. K. Tsang

Performance study of power saving classes of type I and II in IEEE 802.16e

The IEEE 802.16e standard introduces two types of sleep modes which perform very differently under different traffic types: Power Saving Classes of Type I based on binaryincreasing sleep window size and Power Saving of Type II using constant sleep window size. This paper provides simple but accurate analytical models capable of calculating the power efficiency and packet access delay for the two power saving types. In addition, a comparison of the energy efficiency and delay performance between the two power saving types is reported. By means of the proposed model and evaluation, we point out the trade-off between these two types and suggest a power switching scheme to obtain optimal power efficiency under different traffic conditions. Numerical and simulation results are provided for validation of our models. © 2006 IEEE

Optimal selection of power saving classes in IEEE 802.16e

The new IEEE 802.16e standard introduces two types of sleep modes for energy-efficient operations: Power Saving Classes (PSCs) of type I based on binary-increasing sleep window size and PSCs of type II using constant sleep window size. This paper determines the optimal sleep mode selection for IEEE 802.16e by using the semi-Markov Decision Processes (SemiMDP). By means of evaluating corresponding cost metrics on system energy consumption and delay performance, we highlight the energy-performance trade-offs among different operational modes and formulate it as probabilistic constrained policy optimization (PO) problems. Our main goal is to search the space of all policies and to find the optimal one that achieves the minimum energy cost or traffic delay under different traffic requirements. Numerical results demonstrate the effectiveness of our semi-MDP method. We also investigate how the energy cost, delay penalty, as well as user objective jointly affect the space of the optimal policies. © 2007 IEEE