We present a novel queuing analytical framework for the performance evaluation of a distributed and energy-aware medium access control (MAC) protocol for wireless packet data networks with service differentiation. Specifically, we consider a node (both buffer-limited and energy-limited) in the network with two different types of traffic, namely, high-priority and low-priority traffic, and model the node as a MAP (Markovian arrival process)/PH (phase-type)/1/K nonpreemptive priority queue. The MAC layer in the node is modeled as a server and a vacation queuing model is used to model the sleep and wakeup mechanism of the server. We study standard exhaustive and number-limited exhaustive vacation models both in multiple vacation case. A setup time for the head-of-line packet in the queue is considered, which abstracts the contention and the back-off mechanism of the MAC protocol in the node. A nonideal wireless channel model is also considered, which enables us to investigate the effects of packet transmission errors on the performance behavior of the system. After obtaining the stationary distribution of the system using the matrix-geometric method, we study the performance indices, such as packet dropping probability, access delay, and queue length distribution, for high-priority packets as well as the energy saving factor at the node. Taking into account the bursty traffic arrival (modeled as MAP) and, therefore, the nonsaturation case for the queuing analysis of the MAC protocol, using phase-type distribution for both the service and the vacation processes, and combining the priority queuing model with the vacation queuing model make the analysis very general and comprehensive. Typical numerical results obtained from the analytical model are presented and validated by extensive simulations. Also, we show how the optimal MAC parameters can be obtained by using numerical optimization

A queuing analytical model is presented to investigate the performances of different sleep and wakeup strategies in a solar-powered wireless sensor/mesh network where a solar cell is used to charge the battery in a sensor/mesh node. While the solar radiation process (and, hence, the energy generation process in a solar cell) is modeled by a stochastic process (i.e., a Markov chain), a linear battery model with relaxation effect is used to model the battery capacity recovery process. Developed based on a multidimensional discrete-time Markov chain, the presented model is used to analyze the performances of different sleep and wakeup strategies in a sensor/mesh node. The packet dropping and packet blocking probabilities at a node are the major performance metrics. The numerical results obtained from the analytical model are validated by extensive simulations. In addition, using the queuing model, based on a game-theoretic formulation, we demonstrate how to obtain the optimal parameters for a particular sleep and wakeup strategy. In this case, we formulate a bargaining game by exploiting the trade-off between packet blocking and packet dropping probabilities due to the sleep and wakeup dynamics in a sensor/mesh node. The Nash solution is obtained for the equilibrium point of sleep and wakeup probabilities. The presented queuing model, along with the game-theoretic formulation, would be useful for the design and optimization of energy-efficient protocols for solar-powered wireless sensor/mesh networks under quality-of-service (QoS) constraints

A queueing analysis of a distributed and energy-aware medium access control (MAC) protocol is presented for wireless ad hoc networks with service differentiation. We consider a battery-powered node in the network with two different types of traffic, and model the node as a MAP/PH/1/K non-preemptive priority queue with multiple vacations to model the sleep and wakeup mechanism of the MAC layer as the server of the queues. Taking into account the non-saturation case for the queueing analysis of the MAC protocol, using phase-type distribution for both the service and the vacation processes, and combining the priority queueing model with the vacation queueing model make the analysis very general and comprehensive.

We present a novel analytical framework to investigate the performances of different sleeping strategies in a wireless sensor network where a solar cell is used to charge the battery in a sensor node. While the energy generation process (i.e., solar radiation) in a solar cell is modeled by a stochastic process (i.e., a Markov chain), a linear battery model with relaxation effect is used for the battery capacity recovery process. Average queue length, packet dropping and packet blocking probabilities and packet delay distribution at each node are the major performance metrics. Developed based on a multi-dimensional discrete-time Markov chain, the presented model can be used to analyze the performances of different sleep and wakeup strategies at each node (e.g., strategies based on available battery capacity, channel state, solar radiation condition and queue length, and hybrid of these conditions). The numerical results obtained from the analytical model are validated by extensive simulations. The presented model would be useful for designing and optimizing sleeping strategies in a solar powered sensor network under energy and QoS constraints.

We investigate connection-level and packet-level quality-of-service (QoS) performances in a solar-powered wireless mesh network when a connection admission control (CAC) mechanism is used at each mesh node. A queueing analytical model is developed to evaluate the various performance measures at a mesh node considering a general sleep and wakeup mechanism and constrained power supply at that node. Based on this queueing model, we demonstrate how an optimization problem can be formulated to obtain the optimal sleep and wakeup parameters or the CAC threshold so that the desired QoS performance can be achieved under constrained power supply.

In a distributed multihop mesh/relay network (e.g., wireless ad hoc/sensor network, cellular multihop network), each node acts as a relay node to forward data packets from other nodes. These nodes are often energy-limited and also have limited buffer space. Therefore, efficient power saving mechanisms (e.g., sleeping mechanisms) are required so that the lifetime of these nodes can be extended while at the same time the quality of service (QoS) requirements (e.g., packet delay and packet loss rate) for the relayed packets can be satisfied. In this paper, we present a novel queueing analytical framework to study the tradeoff between the energy saving and the QoS at a relay node. Specifically, by modeling the bursty traffic arrival process as a MAP (Markovian arrival process) and the packet service process as having a phase-type (PH) distribution, we model each node as a MAP/PH/1 nonpreemptive priority queue. The relayed packets and the node's own packets form two priority classes and the medium access control (MAC)/physical (PHY) layer protocol in the transmission protocol stack acts as the server process. Moreover, we use a phase-type vacation model for the energy-saving mechanism in a node when the MAC/PHY protocol refrains from transmitting in order to save battery power. Two different power saving mechanisms due to the standard exhaustive and the number-limited exhaustive vacation models (both in multiple vacation cases) are analyzed to study the tradeoff between the QoS performance of the relayed packets and the energy saving at a relay node. Also, an optimization formulation is presented to design an optimal wakeup strategy for the server process under QoS constraints. We use matrix-geometric method to obtain the stationary probability distribution for the system states from which the performance metrics are derived. Using phase-type distribution for both the service and the vacation processes and combining the priority queueing model with the vacation queueing model make the analysis very general and comprehensive