Sharif Digital Repository

Most of the publications regarding the maxim covering location problem (MCLP) address the case where the decision is to be made for one period. In this paper, we deal with a rather untouched version of MCLP which is called dynamic MCLP (DMCLP). In order to solve this problem, a simulated annealing (SA) has been presented. The proposed solution algorithm is capable of solving problems with up to 2500 demand nodes and 200 potential facilities with a fair amount of exactness. Our experiments showed that the proposed approach finds solutions with errors less than one percent  

This paper presents a model for “Domestic Facility and Hub Location” in transportation network. Number of hubs and facilities are unknown and the objective is to minimize the transportation cost, lost demand penalty and facility set up costs. Also the distribution of demand among domestic facilities and hubs adheres to gravity rule. To solve the problem, sequential and integrated approaches were undertaken. In the sequential approach, domestic facilities were allocated and hubs were selected afterwards. However the integrated approach deals with both concurrently, with a more sophisticated steps reaching to the solution. This is mainly because the demand itself is highly dependent to where... 

The placement of the Last Level Cache (LLC) banks in the GPU on-chip network can significantly affect the performance of memory-intensive workloads. In this paper, we attempt to offer a placement methodology for the LLC banks to maximize the performance of the on-chip network connecting the LLC banks to the streaming multiprocessors in GPUs. We argue that an efficient placement needs to be derived based on a novel metric that considers the latency hiding capability of the GPUs through thread level parallelism. To this end, we propose a throughput aware metric, called Effective Latency Impact (ELI). Moreover, we define an optimization problem to formulate our placement approach based on the... 

Limited energy in each node is the major design constraint in wireless sensor networks (WSNs). To overcome this limit, wireless rechargeable sensor networks (WRSNs) have been proposed and studied extensively over the last few years. In a typical WRSN, batteries in sensor nodes can be replenished by a mobile charger that periodically travels along a certain trajectory in the sensing area. To maximize the charged energy in sensor nodes, one fundamental question is how to control the traveling velocity of the charger. In this paper, we first identify the optimal velocity control as a key design objective of mobile wireless charging in WRSNs. We then formulate the optimal charger velocity... 

5G networks are going to support a variety of vertical services, with a diverse set of key performance indicators (KPIs), by using enabling technologies such as software-defined networking and network function virtualization. It is the responsibility of the network operator to efficiently allocate the available resources to the service requests in such a way to honor KPI requirements, while accounting for the limited quantity of available resources and their cost. A critical challenge is that requests may be highly varying over time, requiring a solution that accounts for their dynamic generation and termination. With this motivation, we seek to make joint decisions for request admission,... 

Current methods of routing are based on network information in the form of routing tables, in which routing protocols determine how to update the tables according to the network changes. Despite the variability of data in routing tables, node addresses are constant. In this paper, we first introduce the new concept of variable addresses, which results in a novel framework to cope with routing problems using heuristic solutions. Then we propose a heuristic routing mechanism based on the application of genes for determination of network addresses in a variable address network and describe how this method flexibly solves different problems and induces new ideas in providing integral solutions...