Sharif Digital Repository

Implanted biomedical sensor networks provide a major application of sensor networks in the near future. Their high temperature due to wireless communication, might damage the surrounding tissues. This paper presents an efficient thermal-aware routing. Our proposed protocol states that when some nodes in the shortest path have a high temperature, ignores this path. The simulation results indicate the superiority of the proposed method compared to other thermal-aware routing protocols in terms of reducing temperature without a significant increase in packet delivery delay and power consumption of nodes. © 2009 IEEE  

This paper studies an iterative stochastic algorithm for solving the stochastic shortest path problem. This algorithm, which uses a distributed learning automata, tries to find the shortest path by taking a sufficient number of samples from the edges of the graph. In this algorithm, which edges to be sampled are determined dynamically as the algorithm proceeds. At each iteration of this algorithm, a distributed learning automata used to determine which edges to be sampled. This sampling method, which uses distributed learning automata, reduces the number of samplings from those edges, which may not be along the shortest path, and resulting in a reduction in the number of the edges to be... 

The critical issue in designing correlated data networks like Wireless Sensor Networks is to minimize the total cost of data transmission in the network, and decrease the amount of data flow. The problem of finding optimal aggregation tree for correlated data gathering in single sink network is considered as an NP-Complete problem and hence heuristic methods are usually applied to solve it[1]. In this paper, we apply genetic algorithm (GA) to solve the problem. In our method, we improve the performance of genetic search by selecting proper initial population. This initial population is determined in two ways, by using Prime's algorithm, and shortest path tree. The main issue is to regard... 

We propose an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost. With rise in demands, advancement in technology and increase in production capacity, the need for more shops persists. Therefore, a flexible jobshop system has more than one shop with the same duty. The difference among shops with the same duty is in their machines with various specifications. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An automated guided vehicle functions as a material handling device through the manufacturing network. To account for uncertainty, we consider... 

Traffic assignment is a step of travel demand estimation. Given a trip origin-destination demand matrix, this step determines traffic flow in each link, according to assumptions based on the behavior of drivers. Conventional assignment algorithms, which are mostly based on the Wardrop first principle of user equilibrium, assume that all drivers choose the shortest path to the destination, based on the same travel time computed by travel time functions. However, in reality, driver perception of travel time varies for a specific route. This paper presents a traffic assignment algorithm which assumes that driver perception of travel time affects route choices. Fuzzy set theory is used to define... 

We propose an approach for finding an optimal path in a flexible jobshop manufacturing system considering two criteria of time and cost. With rise in demands, advancement in technology, and increase in production capacity, the need for more shops persists. Therefore, a flexible jobshop system has more than one shop with the same duty. The difference among shops with the same duty is in their machines with various specifications. A network is configured in which the nodes are considered to be the shops with arcs representing the paths among the shops. An Automated Guided Vehicle (AGV) functions as a material handling device through the manufacturing network. To account for uncertainty, we...