This paper presents a duty cycling based cross layer MAC protocol for wireless sensor networks (WSNs), referred to as BulkMAC, to support the transmission of multihop multiple packet flows during a single sleep period. We show that without the proposed cross-layered approach, the sensor nodes will spend significant energy and induce longer delays. The proposed protocol cleverly schedules the channel allocation using the upper routing layer information. We implement our protocol in ns2.29 and compare it against RMAC (Routing Enhanced MAC Protocol) and PRMAC (Pipelined-RMAC). On the average, BulkMAC improves data delivery by a factor of 2.26 and 1.67 compared to RMAC and PRMAC, respectively, for data collection in random networks.

We describe a novel pipelined routing enhanced MAC protocol (PRMAC) for wireless sensor networks that employs cross layer optimization to realize efficient channel access over multiple hops. The main goal of the protocol is to schedule multi hop transmissions of data packets in a single cycle to reduce end- to-end delay. When nodes are awake, a multi-hop flow is constructed using the information from the routing layer, and data packet transmission is scheduled in the subsequent sleep period. When compared with existing solutions such as RMAC, our ns-2 based simulation results show an average 62.2% reduction in end to end packet delivery time for unicast traffic on random networks and up to 200% improvement in delivery ratio on multi-hop chains.

Collaborative signal processing is one of the most promising applications that are currently being investigated for sensor networks. In this paper, we use FFT computation as a vehicle to highlight the issues involved in realizing distributed computations over sensor networks that have global and local communication and synchronization characteristics. We present a power efficient algorithm for computing 1-D Fast Fourier Transform (FFT) over single and multi-hop wireless sensor networks. The proposed algorithm reduces the number of transmissions, eliminates typical redundant computations in a distributed FFT algorithm and uniformly maps complex multiplications over all the sensors nodes by introducing an extra bit-complement permutation stage after first (log2N)/2 iterations. We show that the proposed algorithm improves energy consumption by 36 % on the average on multi-hop sensor networks. This saving in energy consumption significantly improves the battery life of the sensor nodes thereby increasing lifetime of the sensor network. 1.

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