Decentralized Medium Access Control Research Articles

A MAC Protocol for CR-WSN without a Dedicated Common Control Channel

We present a decentralized medium access control protocol for cognitive radio wireless sensor networks. The proposed protocol allows secondary wireless sensors nodes to recognize spectrum opportunities and transmits data based on the licensed users’ arrival prediction on the channel. It estimates the number of active cognitive wireless sensor nodes and it also adjusts the sleep cycle in order to conserve energy. The proposed protocol does not need a dedicated common control channel to negotiate for the data channels. We evaluate delay, energy consumption, and goodput, which are the three important qualities of service parameters through simulation. The simulation results show that the proposed approach achieves higher energy conservation with a small cost of delay and adequate aggregated goodput.

Queueing Analysis of Polling Based Wireless MAC Protocols with Sleep-Wake Cycles

While decentralized medium access control (MAC) protocols are more popular in wireless environments, cluster based sensor networks are particularly amenable to centralized, polling based protocols. In this paper we present an analytic model to evaluate the performance of polling based MAC protocols for wireless networks in terms of the packet delay, buffer overflow rates and energy consumption. We show that polling based protocols can outperform popular decentralized MAC protocols. Simulation results are presented to validate our model and conclusions.

On the fairness of large CSMA networks

We characterize the fairness of decentralized medium access control protocols based on CSMA/CA, in large multi-hop wireless networks. In particular, we show that the widely observed unfairness of these protocols in small network topologies does not always persist in large topologies. In regular networks, this unfairness is essentially due to the unfair advantage of nodes at the border of the network, which have a restricted neighborhood and thus a higher probability to access the communication channel. In large 1D lattice networks these border effects do not propagate inside the network, and nodes sufficiently far away from the border have equal access to the channel; as a result the protocol is long-term fair. In 2D lattice networks, we observe a phase transition. If the access intensity of the protocol is small, the border effects remain local and the protocol behaves similarly as in one-dimensional networks. However, if the access intensity of the protocol is large enough, the border effects persist independently of the size of the network and the protocol is strongly unfair. In irregular networks, the topology is inherently unfair. This unfairness increases with the access intensity of the protocol, but in a much smoother way than in regular two-dimensional networks. Finally, in situations where the protocol is long-term fair, we provide a characterization of its short-term fairness.

Self-Organization Properties of CSMA/CA Systems and Their Consequences on Fairness

Decentralized medium access control schemes for wireless networks based on CSMA/CA, such as the IEEE 802.11 protocol, are known to be unfair. In multihop networks, they can even favor some links to such an extent that the others suffer from virtually complete starvation. This observation has been reported in quite a few works, but the factors causing it are still not well understood. We find that the capture effect and the relative values of the receive and carrier sensing ranges play a crucial role in the performance of these protocols. Using a simple Markovian model, we show that an idealized CSMA/CA protocol suffers from starvation when the receiving and sensing ranges are equal, but quite surprisingly that this unfairness is reduced or even disappears when these two ranges are sufficiently different. We also show that starvation has a positive counterpart, namely organization. When its access intensity is large the protocol organizes the transmissions in space in such a way that it maximizes the number of concurrent successful transmissions. We obtain exact formula for the so-called spatial reuse of the protocol on large line networks.