The present paper proposes a dynamic spectrum access policy for multi-hop cognitive radio networks (CRNs), where the transmission in each hop suffers a delay waiting for the communication channel to become available. Recognizing the energy constraints, we assume that each secondary user (SU) in the network is powered by a battery with finite initial energy. We develop an energy-efficient policy for CRNs using the Markov decision process, which searches for spectrum opportunities without a common communication channel and assigns each sensor's decision to every time slot. We first consider a single-sensor scenario. Due to the intermittent activation of the sensor, achieving the optimal sensing schedule requires excessive complexity and is computationally intractable, owing to the fact that the state space of the Markov decision process evolves exponentially with time variance. In order to overcome this difficulty, we propose a state-reduced suboptimal policy by relaxing the constrained state space, i.e., assuming that the electrical energy of a node is infinite, because this state-reduced suboptimal approach can substantially reduce the complexity of decision-making for CRNs. We then analyze the performance of the proposed policy and compare it with the optimal solution. Furthermore, we verify the performance of this spectrum access policy under real conditions in which the electrical energy of a node is finite. The proposed spectrum access policy uses the dynamic information of each channel. We prove that this schedule is a good approximation for the true optimal schedule, which is impractical to obtain. According to our theoretical analysis, the proposed policy has less complexity but comparable performance. It is proved that when the operating time of the CRN is sufficiently long, the data reception rate on the sink node side will converge to the optimal rate with probability 1. Based on the results for the single-sensor scenario, the proposed schedule is extended to a multi-hop CRN. The proposed schedule can achieve synchronization between transmitter and receiver without relying on a common control channel, and also has near-optimal performance. The performance of the proposed spectrum access policy is confirmed through simulation.

Peer-to-Peer (P2P) file distribution systems can efficiently disseminate massive contents, such as disk images of operating systems, from a server to many users in a piece-by-piece manner. In particular, the BitTorrent protocol optimizes each peer's download speed by applying the tit-for-tat (TFT) strategy, where each peer preferentially uploads piece(s) to peer(s) from which it can download missing pieces faster. To the best of our knowledge, however, the optimality of TFT-based P2P file distribution has not been studied sufficiently. In this paper, we aim to understand the optimal scheduling in TFT-based P2P file distribution. First, we develop a discrete-time model of TFT-based P2P file distribution and formulate its optimal scheduling as a two-step integer linear programming problem. The first step is to minimize the average file retrieval time among peers, and the second step is to improve fairness among peers. We analyze the optimal solution obtained by the existing solver and reveal the characteristics of the optimal scheduling. Specifically, we show that it is crucial to distribute pieces from the server indirectly to peers with large upload capacity via those with small upload capacity.

A scheduling algorithm aims to minimize the overall execution time of the program by properly allocating and arranging the execution order of the tasks on the core processors such that the precedence constraints among the tasks are preserved. In this paper, we present a new scheduling algorithm by using geometry analysis of the Task Precedence Graph (TPG) based on A* search technique and uses a computationally efficient cost function for guiding the search with reduced complexity and pruning techniques to produce an optimal solution for the allocation/scheduling problem of a parallel application to parallel and multiprocessor architecture. The main goal of this work is to significantly reduce the search space and achieve the optimality or near optimal solution. We implemented the algorithm on general task graph problems that are processed on most of related search work and obtain the optimal scheduling with a small number of states. The proposed algorithm reduced the exhaustive search by at least 50% of search space. The viability and potential of the proposed algorithm is demonstrated by an illustrative example.

This letter shows the performance comparisons of several different rate scheduling schemes for non-real time data service over the uplink of burst switching-based direct sequence code division multiple access (DS/CDMA) system to support the integrated voice/data service. The closed-form solution of optimal scheduling formulation, which minimizes average transmission delay when all of the active data users are transmitting simultaneously, is presented and mathematical analyses with other rate scheduling schemes, which provide efficiency criterion of transmission delay for rate scheduling schemes, are performed. Numerical results show the analyses explicitly.