283 research outputs found

    Towards Optimal Distributed Node Scheduling in a Multihop Wireless Network through Local Voting

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    In a multihop wireless network, it is crucial but challenging to schedule transmissions in an efficient and fair manner. In this paper, a novel distributed node scheduling algorithm, called Local Voting, is proposed. This algorithm tries to semi-equalize the load (defined as the ratio of the queue length over the number of allocated slots) through slot reallocation based on local information exchange. The algorithm stems from the finding that the shortest delivery time or delay is obtained when the load is semi-equalized throughout the network. In addition, we prove that, with Local Voting, the network system converges asymptotically towards the optimal scheduling. Moreover, through extensive simulations, the performance of Local Voting is further investigated in comparison with several representative scheduling algorithms from the literature. Simulation results show that the proposed algorithm achieves better performance than the other distributed algorithms in terms of average delay, maximum delay, and fairness. Despite being distributed, the performance of Local Voting is also found to be very close to a centralized algorithm that is deemed to have the optimal performance

    Learning algorithms for the control of routing in integrated service communication networks

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    There is a high degree of uncertainty regarding the nature of traffic on future integrated service networks. This uncertainty motivates the use of adaptive resource allocation policies that can take advantage of the statistical fluctuations in the traffic demands. The adaptive control mechanisms must be 'lightweight', in terms of their overheads, and scale to potentially large networks with many traffic flows. Adaptive routing is one form of adaptive resource allocation, and this thesis considers the application of Stochastic Learning Automata (SLA) for distributed, lightweight adaptive routing in future integrated service communication networks. The thesis begins with a broad critical review of the use of Artificial Intelligence (AI) techniques applied to the control of communication networks. Detailed simulation models of integrated service networks are then constructed, and learning automata based routing is compared with traditional techniques on large scale networks. Learning automata are examined for the 'Quality-of-Service' (QoS) routing problem in realistic network topologies, where flows may be routed in the network subject to multiple QoS metrics, such as bandwidth and delay. It is found that learning automata based routing gives considerable blocking probability improvements over shortest path routing, despite only using local connectivity information and a simple probabilistic updating strategy. Furthermore, automata are considered for routing in more complex environments spanning issues such as multi-rate traffic, trunk reservation, routing over multiple domains, routing in high bandwidth-delay product networks and the use of learning automata as a background learning process. Automata are also examined for routing of both 'real-time' and 'non-real-time' traffics in an integrated traffic environment, where the non-real-time traffic has access to the bandwidth 'left over' by the real-time traffic. It is found that adopting learning automata for the routing of the real-time traffic may improve the performance to both real and non-real-time traffics under certain conditions. In addition, it is found that one set of learning automata may route both traffic types satisfactorily. Automata are considered for the routing of multicast connections in receiver-oriented, dynamic environments, where receivers may join and leave the multicast sessions dynamically. Automata are shown to be able to minimise the average delay or the total cost of the resulting trees using the appropriate feedback from the environment. Automata provide a distributed solution to the dynamic multicast problem, requiring purely local connectivity information and a simple updating strategy. Finally, automata are considered for the routing of multicast connections that require QoS guarantees, again in receiver-oriented dynamic environments. It is found that the distributed application of learning automata leads to considerably lower blocking probabilities than a shortest path tree approach, due to a combination of load balancing and minimum cost behaviour

    Saturation routing for asynchronous transfer mode (ATM) networks

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    The main objective of this thesis is to show that saturation routing, often in the past considered inefficient, can in fact be a viable approach to use in many important applications and services over an Asynchronous Transfer Mode (ATM) network. For other applications and services, a hybrid approach (one that partially uses saturation routing) is presented. First, the minimum effects of saturation routing are demonstrated by showing that the ratio, defined as f, of routing overhead cells over information cells is small even for large networks. Second, modeling and simulation and M/D/l queuing analysis techniques are used to show that the overall effect on performance when using saturation routing is not significant over ATM networks. Then saturation routing ATM implementation is also provided, with important extensions to services such as multicast routing. After an analytical comparison, in terms of routing overhead, is made between Saturation Routing and the currently proposed Private Network-Network Interface (PNNI) procedure for ATM routing made by the ATM forum. This comparison is made for networks of different sizes (343node and 2401 -node networks) and different number of hierarchical levels (3 and 4 levels of hierarchy). The results show that the higher the number of levels of hierarchy and the farthest (in terms of hierarchical levels) the source and the destination nodes are from each other, the more advantageous saturation routing becomes. Finally, a set of measures of performance for use by saturation routing (or any routing algorithm), as metrics for routing path selection, is proposed. Among these measures, an innovative new measure of performance derived for measuring quality of service provided to Constant Bit Rate (CBR) users (e.g., such as voice and video users) called the Burst Voice Arrival Lag (BVAL) is described and derived

    DRFSD: Directed Restricted Flooding For Secure Data-Aggregation In Wireless Sensor Networks

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    Secured Data Transmission is a major issue in Wireless Sensor Networks (WSNs). In this paper we have proposed Directed Restricted Flooding Protocol (DRFSD) in WSNs. This protocol is better than H-SPREAD (Hybrid Security Protocol for REliable dAta Delivery). In DRFSD, alternate multipaths are selected based on the sensor node, that are placed at 180? direction with the Base Station (BS). This scheme is ef?cient in sending the Data Packets to the Base Station in shorter duration than the H-SPREAD. Simulation Results show that our algorithm approach performs well with respect to latency in comparison with earlier algorithm

    A LOAD-BASED APPROACH TO FORMING A CONNECTED DOMINATING SET FOR AN AD HOC NETWORK

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    Efficient routing in mobile ad hoc networks (MANETs) is highly desired and connected dominating sets (CDS) have been gaining significant popularity in this regard. The CDS based approach reduces the search for a minimum cost path between a pair of source and destination terminals to the set of terminals forming the backbone network. Researchers over the years have developed numerous distributed and localized algorithms for constructing CDSs which minimize the number of terminals forming the backbone or which provide multiple node-disjoint paths between each pair of terminals. However none of this research focuses on minimizing the load at the bottleneck terminal of the backbone network constructed by the CDS algorithms. A terminal becomes a bottleneck if the offered traffic load is greater than its effective transmission rate. In this thesis we analyze the load-based performance of a popular CDS algorithm which has been employed in MANET routing and a k-connected k-dominating set (k-CDS) algorithm and compare it with our new centralized algorithm which has been designed to minimize the load at the bottleneck terminal of the backbone network. We verify the effectiveness of our algorithm by simulating over a large number of random test networks
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