Maximizing multicast lifetime in unreliable wireless ad hoc network

Multicast is an efficient method for transmitting the same packets to a group of destinations. In energy-constrained wireless ad hoc networks where nodes are powered by batteries, one of the challenging issues is how to prolong the multicast lifetime. Most of existing work mainly focuses on multicast lifetime maximization problem in wireless packet loss-free networks. However, this may not be the case in reality. In this paper, we are concerned with the multicast lifetime maximization problem in unreliable wireless ad hoc networks. To solve this problem, we first define the multicast lifetime as the number of packets transmitted along the multicast tree successfully. Then we develop a novel lifetime maximization genetic algorithm to construct the multicast tree consisting of high reliability links subject to the source and destination nodes. Simulation results demonstrate the efficiency and effectiveness of the proposed algorithm.     

Data aggregated maximum lifetime routing for wireless sensor networks

In this paper, we present a data aggregated maximum lifetime routing scheme for wireless sensor networks. We address the problem of jointly optimizing data aggregation and routing so that the network lifetime can be maximized. A recursive smoothing method is adopted to overcome the non-differentiability of the objective function. We derive the necessary and sufficient conditions for achieving the optimality of the optimization problem and design a distributed gradient algorithm accordingly. Extensive simulations are carried out to show that the proposed algorithm can significantly reduce the data traffic and improve the network lifetime. The convergence property of the algorithm is studied under various network configurations.     

单频网多播系统中的开环半动态功率分配算法

在单频网多播传输中,传统的全反馈动态功率分配数算法需要根据每个时隙反馈的用户瞬时信道信息进行实时的调整,所以造成了资源分配频率快、上行反馈开销大的缺点。为了克服这个缺点,提出了一个低复杂度、没有用户反馈的单频网多播开环半动态功率分配算法。首先在各小区等功率分配的假设下,根据单频网的形状信息算出各小区等价信道增益,然后再根据这个增益值,实现满足速率需求情况下的各小区功率分配。仿真结果显示,与全反馈的动态功率分配算法相比,该算法以一小部分性能损失为代价,大大减少了单频网的上行反馈和资源分配的开销,因此更适用于实际的单频网多播系统。     

A network selection scheme for multicast applications in wireless network convergence

In wireless network convergence, each mobile host is expected to have multiple kinds of wireless interfaces. Multicast‐based applications are expected to be widely deployed. In this paper, a new network selection scheme is proposed for a mobile host to select the most appropriate wireless access network to maximize user satisfaction and ISP's profit, simultaneously. We have devised a metric to measure a user's satisfaction and we also developed a ‘normalized network resource’ metric for system profit measure. We have compared our scheme with three other reference schemes, through simulations. Depending on the network deployment situations, our scheme exhibits one‐fifth service disruption time of other reference schemes, while the resource consumption of our scheme is comparable to that of the minimum resource scheme. Overall, the gain of our scheme becomes higher as users move faster and/or the population density increases. Copyright © 2010 John Wiley & Sons, Ltd.     

On achieving maximum multicast throughput in undirected networks

The transmission of information within a data network is constrained by the network topology and link capacities. In this paper, we study the fundamental upper bound of information dissemination rates with these constraints in undirected networks, given the unique replicable and encodable properties of information flows. Based on recent advances in network coding and classical modeling techniques in flow networks, we provide a natural linear programming formulation of the maximum multicast rate problem. By applying Lagrangian relaxation on the primal and the dual linear programs (LPs), respectively, we derive a) a necessary and sufficient condition characterizing multicast rate feasibility, and b) an efficient and distributed subgradient algorithm for computing the maximum multicast rate. We also extend our discussions to multiple communication sessions, as well as to overlay and ad hoc network models. Both our theoretical and simulation results conclude that, network coding may not be instrumental to achieve better maximum multicast rates in most cases; rather, it facilitates the design of significantly more efficient algorithms to achieve such optimality.     

Polynomial time algorithms for multicast network code construction

The famous max-flow min-cut theorem states that a source node s can send information through a network (V, E) to a sink node t at a rate determined by the min-cut separating s and t. Recently, it has been shown that this rate can also be achieved for multicasting to several sinks provided that the intermediate nodes are allowed to re-encode the information they receive. We demonstrate examples of networks where the achievable rates obtained by coding at intermediate nodes are arbitrarily larger than if coding is not allowed. We give deterministic polynomial time algorithms and even faster randomized algorithms for designing linear codes for directed acyclic graphs with edges of unit capacity. We extend these algorithms to integer capacities and to codes that are tolerant to edge failures.     

A utility-based distributed maximum lifetime routing algorithm for wireless networks

Energy-efficient routing is a critical problem in multihop wireless networks due to the severe power constraint of wireless nodes. Despite its importance and many research efforts toward it, a distributed routing algorithm that maximizes network lifetime is still missing. To address this problem, this paper proposes a novel utility-based nonlinear optimization formulation to the maximum lifetime routing problem. Based on this formulation, a fully distributed localized routing algorithm is further presented, which is proved to converge at the optimal point, where the network lifetime is maximized. Solid theoretical analysis and simulation results are presented to validate the proposed solution.     

A framework for the multicast lifetime maximization problem in energy-constrained wireless ad-hoc networks

We consider the problem of maximizing the lifetime of a given multicast connection in wireless networks that use directional antennas and have limited energy resources. We provide a globally optimal solution to this problem for a special case of using omni-directional antennas. This graph theoretic approach provides us insights into more general case of using directional antennas, and inspires us to produce a group of heuristic algorithms. Experimental results show that our algorithms outperform other energy-aware multicast algorithms significantly in terms of multicast lifetime.

Interference coordination schemes for cellular network assisted device-to-device multicast

In this paper, a multicast concept for device-to-device （D2D） communication underlaying a cellular infrastruc~tre is investigated. To increase the overall capacity and improve resource utilization, a novel interference coordination scheme is proposed. The proposed scheme includes two steps. First, in order to mitigate the interference from D2D multicast transmission to cellular networks （CNs）, a dynamic power control scheme is proposed that can determine the upper bound of D2D transmitter power based on the location of base station （BS） and areas of adjacent cells from the coverage area of D2D multicast group. Next, an interference limited area control scheme that reduces the interference from CNs to each D2D multicast receiver is proposed. The proposed scheme does not allow the coexistence of cellular user equipments （CUEs） located in the interference limited area to reuse the same resources as the D2D multicast group. From the simulation results, it is confirmed that the proposed schemes improve the performance of the hybrid system compared to the conventional ways.     

基于网络编码的非等长多播数据分发策略

提出了一种新的编码数据分发算法,该算法通过收集每个多播路径簇上承载业务信息的带宽,来确定编码后数据的分发策略,使编码节点能够对带宽不相同的数据进行处理并在解码节点正确解码,从而更加贴近现实网络.仿真结果表明,该算法在资源消耗和网络均衡方面较传统的多播算法有更好的表现.     

Egocentric network focused community aware multicast routing for DTNs

Multicasting for delay-tolerant networks (DTNs) in sparse social network scenarios is a challenge due to the deficiency of end-to-end paths. In social network scenarios, the behaviors of their nodes are controlled by human beings, and node mobility is the same as that of humans. To design the multicasting algorithms for DTNs, therefore, it would be promising to capture the intrinsic characteristics of relationships among these nodes. In this paper, multicasting in DTNs is regarded as a message dissemination issue in social networks, and an egocentric network focused community aware multicast routing algorithm (ENCAR) is proposed. As distinct from some social-based routing algorithms which only focus on centrality analysis, ENCAR is an utility based and hierarchical routing algorithm, its utility function is constructed on the basis of centrality analysis and destination-oriented contact probability. We take notice of clustering phenomenon in social networks, and present the community aware forwarding schemes. In addition, to simulate the mobility of individuals in social networks, a novel community based random way point mobility model is also presented. In this paper, the performance of ENCAR is theoretically analyzed and further evaluated on simulator ONE. Simulation results show that ENCAR outperforms most of the existing multicast routing algorithms in routing overhead, on condition that delivery ratio is relatively high, with other significant parameters guaranteed to perform well.     

Distributed probabilistic routing for sensor network lifetime optimization

A probabilistic and distributed routing approach for multi-hop sensor network lifetime optimization is presented in this paper. In particular, each sensor self-adjusts their routing probabilities locally to their forwarders based on its neighborhood knowledge, while aiming at optimizing the overall network lifetime (defined as the elapsed time before the first node runs out of energy). The theoretical feasibility and a practical routing algorithm are presented. Specifically, a sufficient distributed condition regarding the neighborhood state for distributed probabilistic routing to achieve the optimal network lifetime is presented theoretically. Based on it, a distributed adaptive probabilistic routing (DAPR) algorithm, which considered both the transmission scheduling and the routing probability evolvement is developed. We prove quantitatively that DAPR could lead the routing probabilities of the distributed sensors to converge to an optimal state which optimizes the network lifetime. Further, when network dynamics happen, such as topology changes, DAPR can adjust the routing probabilities quickly to converge to a new state for optimizing the remained network lifetime. We presented the convergence speed of DAPR. Extensive simulations verified its convergence and near-optimal properties. The results also showed its quick adaptation to both the network topology and data rate dynamics.     

Scheduling algorithms for extending directional sensor network lifetime

Recently, directional sensor networks that are composed of a large number of directional sensors have attracted a great deal of attention. The main issues associated with the directional sensors are limited battery power and restricted sensing angle. Therefore, monitoring all the targets in a given area and, at the same time, maximizing the network lifetime has remained a challenge. As sensors are often densely deployed, a promising approach to conserve the energy of directional sensors is developing efficient scheduling algorithms. These algorithms partition the sensor directions into multiple cover sets each of which is able to monitor all the targets. The problem of constructing the maximum number of cover sets has been modeled as the multiple directional cover sets (MDCS), which has been proved to be an NP-complete problem. In this study, we design two new scheduling algorithms, a greedy-based algorithm and a learning automata (LA)-based algorithm, in order to solve the MDCS problem. In order to evaluate the performance of the proposed algorithms, several experiments were conducted. The obtained results demonstrated the efficiency of both algorithms in terms of extending the network lifetime. Simulation results also revealed that the LA-based algorithm was more successful compared to the greedy-based one in terms of prolonging network lifetime.     

Trading sensing coverage for an extended network lifetime

One of the main benefits of using Wireless Sensor Networks (WSNs) is that they can be deployed in remote locations without any prior infrastructure. Because of this nodes are normally battery powered. This limits the lifetime of the network. In this paper, we propose a novel method of scheduling nodes based on a user’s sensing coverage requirement. Through the use of our proposed scheduling algorithm (Ncut-GA), it is shown that the duration for which the user’s coverage requirement is met can be extended. When compared with a previously published algorithm (Greedy-MSC), the proposed algorithm is able to increase coverage duration by up to 80%. Furthermore it is also shown that the time until the first node dies can be improved by up to 200% through the use of Ncut-GA.     

The use of end-to-end multicast measurements for characterizinginternal network behavior

We present a novel methodology for identifying internal network performance characteristics based on end-to-end multicast measurements. The methodology, solidly grounded on statistical estimation theory, can be used to characterize the internal loss and delay behavior of a network. Measurements on the MBone have been used to validate the approach in the case of losses. Extensive simulation experiments provide further validation of the approach, not only for losses, but also for delays. We also describe our strategy for deploying the methodology on the Internet. This includes the continued development of the National Internet Measurement Infrastructure to support RTP-based end-to-end multicast measurements and the development of software tools to analyze the traces. Once complete, this combined software/hardware infrastructure will provide a service for understanding and forecasting the performance of the Internet     

A copy network with shared buffers for large-scale multicast ATMswitching

An architecture for the copy network that is an integral part of multicast ATM switches is described. The architecture makes use of the property that the broadcast banyan network (BBN) is nonblocking if the active inputs are cyclically concentrated and the outputs are monotone. In the architecture, by employing a token ring reservation scheme, the outputs of the copy network are reserved before a multicast cell is replicated. By the copy principle, the number of copies requested by a multicast call is not limited by the size of the copy network so that very large multicast switches can be configured in a modular fashion. The sequence of cells is preserved in the structure. Though physically separated, buffers within the copy network are completely shared, so that the throughput can reach 100%, and the cell delay and the cell loss probability can be made to be very small. The cell delay is estimated analytically and by computer simulation, and the results of both are found to agree with each other. The relationship between the cell loss probability under various traffic parameters and buffer sizes is studied by computer simulation     

Efficient wireless multicast retransmission using network coding

In wireless multicast,network coding has recently attracted attentions as a substantial improvement to packet retransmission schemes.However,the problem of finding the optimal network code which minimizes the retransmissions is hard to solve or approximate.This paper presents two schemes to reduce the number of retransmissions for reliable multicast efficiently.One is retransmission using network coding based on improved Vandermonde matrix(VRNC),the other is retransmission using network coding based on adaptive improved Vandermonde matrix(AVRNC).Using VRNC scheme the sender selects the packets all receivers have lost and encodes them with improved Vandermonde matrix;when receivers receive enough encoded retransmission packets,all the lost packets can be recovered.With AVRNC scheme,the sender can obtain the recovery information from all the receivers after sending out per retransmission packet,and then the improved Vandermonde matrix can be updated,thus reducing the complexity of encoding and decoding.Our proposed schemes can achieve the theoretical lower bound assuming retransmission packets lossless,and approach the theoretical lower bound considering retransmission packets loss.Simulation results show that the proposed algorithms can efficiently reduce the number of retransmissions,thus improving transmission efficiency.