Current Issue : January - March Volume : 2015 Issue Number : 1 Articles : 6 Articles
Ad hoc networks are wireless mobile networks that can operate without infrastructure and without centralized\nnetwork management. Traditional techniques of routing are not well adapted. Indeed, their lack of reactivity with\nrespect to the variability of network changes makes them difficult to use. Moreover, conserving energy is a critical\nconcern in the design of routing protocols for ad hoc networks because most mobile nodes operate with limited\nbattery capacity, and the energy depletion of a node affects not only the node itself but also the overall network\nlifetime. In all proposed single-path routing schemes, a new path-discovery process is required once a path failure is\ndetected, and this process causes delay and wastage of node resources. A multipath routing scheme is an alternative\nto maximize the network lifetime. In this paper, we propose an energy-efficient multipath routing protocol, called ad\nhoc on-demand multipath routing with lifetime maximization (AOMR-LM), which preserves the residual energy of\nnodes and balances the consumed energy to increase the network lifetime. To achieve this goal, we used the residual\nenergy of nodes for calculating the node energy level. The multipath selection mechanism uses this energy level to\nclassify the paths. Two parameters are analyzed: the energy threshold ? and the coefficient ?. These parameters are\nrequired to classify the nodes and to ensure the preservation of node energy. Our protocol improves the performance\nof mobile ad hoc networks by prolonging the lifetime of the network. This novel protocol has been compared with\nother protocols: ad hoc on-demand multipath distance vector (AOMDV) and ZD-AOMDV. The protocol performance\nhas been evaluated in terms of network lifetime, energy consumption, and end-to-end delay....
Compressive sensing (CS) has given us a new idea at data acquisition and signal processing. It has proposed some\nnovel solutions in many practical applications. Focusing on the pixel-level multi-source image-fusion problem in\nwireless sensor networks, the paper proposes an algorithm of CS image fusion based on multi-resolution analysis. We\npresent the method to decompose the images by nonsubsampled contourlet transform (NSCT) basis function and\nwavelet basis function successively and fuse the images in compressive domain. It means that the images can be sparsely\nrepresented by more than one basis function. We named this process as blended basis functions representation. Since\nthe NSCT and wavelet basis functions have complementary advantages in multi-resolution image analysis, and the signals\nare sparser after being decomposed by two kinds of basis functions, the proposed algorithm has perceived advantages in\ncomparison with CS image fusion in wavelet domain which is widely reported by literatures. The simulations show that\nour method provides promising results....
To satisfy the ever-increasing data rate and service coverage demands, wireless communication networks evolve into\nheterogeneous networks (HetNets), where low-cost small base stations are embedded in conventional macrocells.\nIntercell interference emerges as the key capacity-limiting factor in such dense networks, restricting the reusability of\nspectral resources. Therefore, advanced interference mitigation techniques relying on multi-cell cooperation have\nattracted significant attention from the wireless industry and academia. This paper discusses interference\nmanagement schemes for multi-tiered spectrum access in next-generation HetNets. A novel scheme based on full\nsystem cognition and base station cooperation is proposed as an enabler for high-capacity HetNets. In addition,\npractical implementation and operational challenges are investigated....
Many geographic routing algorithms have been proposed for vehicular ad hoc networks (VANETs), which have the\nstrength of not maintaining any routing structures. However, most of which rely on the availability of accurate real-time\nlocation information. It is well known that vehicles can be intermittently connected with other vehicles. Thus, in such\nnetworks, it is difficult or may incur considerable cost to retrieve accurate locations of moving vehicles. Furthermore,\nthe location information of a moving vehicle available to other vehicles is usually time-lagged since it is constantly\nmoving over time. Fortunately, we observe that the short-term future locations of vehicles can be predicted. Based on\nthe important observation, we propose a novel approach for geographic routing which exploits the predictive\nlocations of vehicles. Thus, we have developed a prediction technique based on the current speed and heading\ndirection of a vehicle. As a result, the request frequency of location updates can be reduced. In addition, we propose\ntwo forwarding strategies and three buffer management strategies. We have performed extensive simulations based\non real vehicular GPS traces collected from around 4,000 taxis in Shanghai, China. Simulation results clearly show that\ngeographic routing based on predictive locations is viable and can significantly reduce the cost of location updates...
Delay-tolerant networks (DTNs) are wireless partitioned networks. Because of intermittency, mobile ad hoc network\n(MANET) routing protocols are not efficient in DTNs. Wildlife tracking, vehicular networks, interplanetary networks,\netc. are different applications of DTN. Regarding DTN applications, different parameters should be considered while\ndesigning DTN routing protocols. Message delivery ratio, message delivery delay, overhead, message drop, etc. are\nsome important factors that are usually considered in routing algorithms. This paper proposes a method which tries\nto reduce overhead and message drop while increasing message delivery ratio. Choosing the appropriate number\nof message copies to distribute in the network is important. Few numbers of copies can lead to message drop. So,\nthe message cannot be delivered to the destination. On the other hand, increasing the number of copies causes\noverhead increase in the network. The proposed algorithm uses particle swarm optimization (PSO) in intelligent\nchoosing of number of message copies. Regarding message delivery ratio and network overhead, PSO greatly helps\nin finding the suitable number of copies. In order to evaluate our method, which is called PSODTN, we compared it\nwith epidemic routing (ER) and probabilistic routing protocol using history of encounters and transitivity (PROPHET).\nPSODTN helps to reduce overhead, on average, 95.6% compared to ER and PROPHET. While reducing overhead,\nPSODTN message delivery ratio is on average 98%....
We consider in this paper downlink scheduling for different traffic classes at the MAC layer of wireless systems based\non orthogonal frequency division multiple access (OFDMA), such as the recent 3rd Generation Partnership Project\n(3GPP) long-term evolution (LTE)/LTE-A wireless standard. Our goal is to provide via the scheduling decisions quality\nof service (QoS), but also to guarantee fairness among the different users and traffic classes (including delay-sensitive\nand best-effort traffic). QoS-aware scheduling strategies, such as modified largest weighted delay first (M-LWDF),\nexponential (EXP), exponential proportional fair (EXP-PF), and the log-based scheduling rules, prioritize delay-sensitive\ntraffic by considering rules based on the head-of-line (HoL) packet delay and the tolerated packet loss rate, whereas\nthey serve best-effort traffic by considering the classical proportional fair (PF) rule. These scheduling rules do not\nprevent resource starvation for best-effort traffic. On the other side, if both traffic types are scheduled according to the\nPF rule, then delay-sensitive flows suffer from delay bound violations. In order to fairly distribute the resources among\ndifferent service classes according to their QoS requirements and channel conditions, we employ the concept of fuzzy\nlogic in our scheduling framework. By employing the fuzzy logic concept, we serve all the traffic classes with one\npriority rule. Simulation results show better intra-class and inter-class fairness than state-of-the-art scheduling rules.\nThe proposed scheduling framework enables to appropriately balance delay requirements of traffic, system\nthroughput, and fairness....
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