Md. Mostofa Akbar

Solving the Multidimensional Multiple-choice Knapsack Problem by constructing convex hulls

This paper presents a heuristic to solve the Multidimensional Multiple-choice Knapsack Problem (MMKP), a variant of the classical 0-1 Knapsack Problem. We apply a transformation technique to map the multidimensional resource consumption to single dimension. Convex hulls are constructed to reduce the search space to find the near-optimal solution of the MMKP. We present the computational complexity of solving the MMKP using this approach. A comparative analysis of different heuristics for solving the MMKP has been presented based on the experimental results.

Heuristic Solutions for the Multiple-Choice Multi-dimension Knapsack Problem

The Multiple-Choice Multi-Dimension Knapsack Problem (MMKP) is a variant of the 0-1 Knapsack Problem, an NP-Hard problem. Hence algorithms for finding the exact solution of MMKP are not suitable for application in real time decision-making applications, like quality adaptation and admission control of an interactive multimedia system. This paper presents two new heuristic algorithms, M-HEU and I-HEU for solving MMKP. Experimental results suggest that M-HEU finds 96% optimal solutions on average with much reduced computational complexity and performs favorably relative to other heuristic algorithms for MMKP. The scalability property of I-HEU makes this heuristic a strong candidate for use in real time applications.

Intelligent Mobile Health Monitoring System (IMHMS)

Health monitoring is repeatedly mentioned as one of the main application areas for Pervasive computing. Mobile Health Care is the integration of mobile computing and health monitoring. It is the application of mobile computing technologies for improving communication among patients, physicians, and other health care workers. As mobile devices have become an inseparable part of our life it can integrate health care more seamlessly to our everyday life. It enables the delivery of accurate medical information anytime anywhere by means of mobile devices. Recent technological advances in sensors, low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight and intelligent bio-sensor nodes. These nodes, capable of sensing, processing, and communicating one or more vital signs, can be seamlessly integrated into wireless personal or body area networks for mobile health monitoring. In this paper we present Intelligent Mobile Health Monitoring System (IMHMS), which can provide medical feedback to the patients through mobile devices based on the biomedical and environmental data collected by deployed sensors.

Extended-butterfly fat tree interconnection (EFTI) architecture for network on chip

System on chip (SoC) design requires efficient communication between heterogeneous resources to meet the high-speed transmission needs. Therefore one of the key factors for the success of ultra-deep submicron technologies will be the capability of integrating different resources like processor core, memory, an FPGA, a custom hardware block or any other semiconductor intellectual property (SIP) block into a single piece of silicon. Non-scalable global wire delays, global synchronization failure, loss of signal integrity issues are the main problems. To address these problems, various interconnect architectures are proposed. Butterfly fat tree (BFT) is one of those. To improve the performance of BFT we introduce extended-butterfly fat tree interconnection (EFTI). Routing algorithm is provided for EFTI and comparative analysis is performed through the simulation result.

Gpnocsim - A General Purpose Simulator for Network-On-Chip

Network-on-chip (NoC) has gained considerable attention over the last few years as a paradigm for implementing communication among the system components embedded in a single chip. As such, there has been an increased need for defining and developing simulation software for carrying out simulation of NoC architectures. In this paper, we present gpNoCsim, a Java based general-purpose network simulator for NoC, which is built upon the object-oriented modular design of the NoC architecture components. Here we demonstrate the use of our proposed simulator by simulating several existing well-known architectures. We have also provided the guidelines on how to simulate future architectures. Finally, we have validated the outputs of gpNoCsim with the studies of existing NoC architectures.

Addressing Techniques in Wireless Sensor Networks: A Short Survey

Wireless sensor networks consist of many small nodes with sensing, computation and communication capabilities. Being organized into a network, sensors perform some distributed sensing operation in a target area. Addressing problem focuses on dynamic allocation of addresses to sensor nodes. In this paper, the authors present a short survey of the state-of-the-art addressing techniques for sensor networks that frequently appear in the literature. The authors classify the addressing techniques and describe individual scheme with the specific objective of the scheme. The authors also study the design trade-offs considered by the respective schemes and make a comparison among the techniques.

Heuristic algorithm of the multiple-choice multidimensional knapsack problem (MMKP) for cluster computing

This paper presents two heuristic algorithms of the MMKP (a variant of 0–1 knapsack problem) for cluster computing. We present an architecture of a cluster, such that algorithm requires small message passing. The algorithms divide the problem among computational nodes. Each node solves its sub problem using a sequential heuristic. This naïve divide and conquer approach cannot achieve good revenue. The revenue is the value achieved by the solution of MMKP. To improve the revenue, it accumulates the unused resources from every node, and assigns to the node, which gives maximum revenue over all nodes. This is the residue exploitation (RE) strategy. The solution quality can be improved by a novel resource-division policy rather than equal division. The policy divides the resource among all nodes such that total revenue increases. A sequential heuristic calculates the solution incrementally for different amounts of resource capacity, and the best combination is taken as the solution. This is the resource adjustment (RA) strategy. We experiment the algorithm using MPI (Message Passing Interface). The proposed algorithms show encouraging results.

Controlling remote system using mobile telephony

In modern days, we have to be in touch with various high-tech machineries and equipments to get our jobs done and make our lives easier. Too often these machineries serve very important purposes and sometimes require continuous monitoring. But its not always feasible to be physically near to the system. So, to be in touch with this sort of important systems by not being physically close, we need some sort of remote solution. The remote solution should unleash the restrictions due to physical distance yet provides enough reliability even from distance. Some products are commercially available which allow remote systems controlling through internet which is undoubtedly emerging; yet, it lacks the true sense of real mobility and security, making the remote system controlling a limited term than it is supposed to be. In search of true a remote and adequately secure solution to be really effective and practicable, which can be a better choice to mobile telephony? Mobile phones have become almost an inseparable part of civil lives today. In this paper we introduce the mechanism so that the ordinary services of the mobile phones can be leveraged to communicate with and control the remote systems.

A new approach to schedule workflow applications for advance reservation of resources in grid

Advance Reservation AR of resources in grid systems allows users to secure resources prior to executing their jobs. This is very important, specially for time critical and workflow applications. One major challenge for applications having interdependent tasks is to minimise the delay of execution of the whole application. In general, the problem of mapping a set of interdependent tasks on distributed services is a NP-complete problem. Thus, in practice, heuristics are most often used to schedule workflow applications in grid. We have exploited some important properties like slack time, critical path of workflow applications to provide a scheduling algorithm that reduces the average delay to complete execution of an application, increases the number of zero delayed applications and takes less average time to run. The system has been designed to support advance reservation of resources. Our proposed system is more fault tolerant and addresses this problem efficiently.

A Permission Based Hierarchical Algorithm for Mutual Exclusion

Due to the growing application of peer-to-peer computing, the distributed applications are continuously spreading over extensive number of nodes. To cope with this large number of participants, various cluster based hierarchical solutions have been proposed. Cluster based algorithms are scalable by nature. Several of them are quorum based solutions. All of these solutions exploit the idea of coordinator/leader of cluster. Thus, fault tolerance of these algorithms is low. If any coordinator fails, election of new one is required. Here we propose a cluster based network architecture of two layers of hierarchy and present a hierarchical permission based algorithm, which is free of coordinator use. We simulate our proposed algorithm and show that it outperforms related ME algorithms.