An On Demand Queue Management Architecture for a Programmable Traffic Manager

A queue manager (QM) is a core traffic management (TM) function used to provide per-flow queuing in access andmetro networks; however current designs have limited scalability. An on-demand QM (OD-QM) which is part of a new modular field-programmable gate-array (FPGA)-based TM is presented that dynamically maps active flows to the available physical resources; its scalability is derived from exploiting the observation that there are only a few hundred active flows in a high speed network. Simulations with real traffic show that it is a scalable, cost-effective approach that enhances per-flow queuing performance, thereby allowing per-flow QM without the need for extra external memory at speeds up to 10 Gbps. It utilizes 2.3%–16.3% of a Xilinx XC5VSX50t FPGA and works at 111 MHz.

Swarm scheduling approaches for work-flow applications with security constraints in distributed data-intensive computing environments

The scheduling problem in distributed data-intensive computing environments has become an active research topic due to the tremendous growth in grid and cloud computing environments. As an innovative distributed intelligent paradigm, swarm intelligence provides a novel approach to solving these potentially intractable problems. In this paper, we formulate the scheduling problem for work-flow applications with security constraints in distributed data-intensive computing environments and present a novel security constraint model. Several meta-heuristic adaptations to the particle swarm optimization algorithm are introduced to deal with the formulation of efficient schedules. A variable neighborhood particle swarm optimization algorithm is compared with a multi-start particle swarm optimization and multi-start genetic algorithm. Experimental results illustrate that population based meta-heuristics approaches usually provide a good balance between global exploration and local exploitation and their feasibility and effectiveness for scheduling work-flow applications. © 2010 Elsevier Inc. All rights reserved.

Development tools for opportunistic pervasive computing

The goal of the POBICOS project is a platform that facilitates the development and deployment of pervasive computing applications destined for networked, cooperating objects. POBICOS object communities are heterogeneous in terms of the sensing, actuating, and computing resources contributed by each object. Moreover, it is assumed that an object community is formed without any master plan; for example, it may emerge as a by-product of acquiring everyday, POBICOS-enabled objects by a household. As a result, the target object community is, at least partially, unknown to the application programmer, and so a POBICOS application should be able to deliver its functionality on top of diverse object communities (we call this opportunistic computing). The POBICOS platform includes a middleware offering a programming model for opportunistic computing, as well as development and monitoring tools. This paper briefly describes the tools produced in the first phase of the project. Also, the stakeholders using these tools are identified, and a development process for both the middleware and applications is presented. © 2009 IEEE.

Unconventional Computing: A Boolean Chemical Perspective

Elementary computing operations can be arranged within molecules so that problems in chemical, biochemical, and biological situations can be addressed. Problems that are found in small and/or living spaces, where the corresponding semiconductor logic devices cannot operate conveniently, are particularly amenable to this approach. The visualization and monitoring of intracellular species is one such category. Problems in medical diagnostics and therapy form additional categories. Chemists and biologists employ chemical synthesis and molecular biology techniques to build molecular logic devices. The photochemical approach to molecular logic devices is particularly prevalent. The fluorescent photoinduced electron transfer (PET) switching principle is particularly useful for designing logic functions into small molecules.