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An ad hoc network (MANET) has no fixed networking infrastructure, and consists of mobile nodes that communicate with each other. Since nodes are mobile, Routing in ad hoc network is a challenging task. Efficient routing protocols can make better performance in such networks. Many protocols have been proposed for ad hoc networks which the most common types are: Ad hoc on-demand Distance Vector (AODV), Dynamic Source Routing (DSR), Optimized Link State Routing (OLSR). In this paper, we introduce a new Position and Neighborhood based Routing (PNR) algorithm for mobile ad hoc networks which uses GPS and new algorithm to reduce the overhead caused by position update messages. We also compare our scheme with DSR, AODV, OLSR for two metrics: packet delivery ratio and end-to-end delay. We use GlomoSim [1] to evaluate these protocols. [ABSTRACT FROM AUTHOR]

Maintenance of the cache consistency is a complicated issue in the wireless mobile environment. Caching of frequently accessed data items on the node can reduce the bandwidth requirement of the mobile node environment. In this paper, we present a new technique called Modified Energy Efficient Cache Invalidation Algorithm (MEECIA) especially to reduce the uplink bandwidth consumption in the wireless ad-hoc network, by choosing following modes: Slow, Fast, Super-fast. The mode is selected based on threshold specified for time and the number of node requesting the updated data to other node. Simulation results demonstrate that our algorithm is efficient in improving mobile caching, reducing the communication bandwidth and also efficiently utilizing the energy in ad-hoc network. Compared to the previously reported cache based Invalidation Report (IR), our scheme can significantly improve the performance in terms of energy consumption and reduce the query latency in ad-hoc network. [ABSTRACT FROM AUTHOR]

In this paper we propose an approach to improve the performance of existing flood based routing algorithm Ad-hoc on demand Distance Vector Routing [2] for mobile Ad-hoc wireless networks based on heuristic searching technique. Flooding technique is often used for route discovery in on demand mechanism in MANET such as AODV, DSR. To avoid the problem of wireless broadcast storm, the heuristic searching approach was introduced in the process of finding route from source node to destination node. Heuristic function considers the characteristics of MANET (Bandwidth, number of nodes in the given range). If a node S wants to send a packet to D in the flooding method S sends packet to all its neighbor nodes, but in the proposed scheme tries to reduce broadcasting by finding heuristic measures of the neighbors of S. The heuristic measures are evaluated by applying a function to all neighbors. [ABSTRACT FROM AUTHOR]

This paper proposes a new discrete-time queue analytical model based on BLUE algorithm in order to determine the network congestion in preliminary stages. We compare the original BLUE, which has been implemented in Java, with our proposed analytical model with regards to different performance measures (average queue length, throughput, average queueing delay and packet loss probability). The comparison results show that the proposed discrete-time queue analytical model outperforms BLUE algorithm in terms of throughput and packet loss probability. Moreover, the proposed model maintains the throughput performance regardless whether the amount of the traffic load is light or heavy. Furthermore, we calculate the packet dropping probability function for our analytical model and the BLUE algorithm in order to decide which algorithm drops fewer packets. [ABSTRACT FROM AUTHOR]

Crossbars are main components of communication switches used to construct interconnection networks. Scheduling algorithm controls contention in switch architecture. Several scheduling algorithms were proposed for input-queued crossbar switch architectures. This paper suggests a Dynamic Scheduling Algorithm (DSA). This algorithm changes the priority rotation dynamically based on two parameters: queue occupancy and quality of service of input and output. DSA efficiently utilizes the buffers and at the same time gives good service to the selected inputs and outputs. The simulation results show that DSA saves loss of the cells due to buffer overflow and thus increases the throughput by 2% to 4% compared to its counter part. DSA reduces the latency for prescribed Quality of Service class input output and increases the average latency. [ABSTRACT FROM AUTHOR]