Improved genetic algorithms and list scheduling techniques for independent task scheduling in distributed systems

Given a set of tasks with certain characteristics, e.g., data size, estimated execution time and a set of processing nodes with their own parameters, the goal of task scheduling is to allocate tasks at nodes so that the total makespan is minimized. The problem has been studied under various assumptions concerning task and node parameters with the resulting problem statements usually being NP-complete. List scheduling (LS) heuristics such as MaxMin and MinMin together with genetic algorithms (GAs) were applied in the past to find solutions. In this paper we investigate new heuristics for both the LS and the GA paradigm with the specific aim of improving the performance of the standard algorithms when task computations involve large data transfers. Experimental results under various environment assumptions illustrate the merits of the new algorithms. © 2007 IEEE

Continuous replica placement schemes in distributed systems

The Replica Placement Problem (RPP) aims at creating a set of duplicated data objects across the nodes of a distributed system in order to optimize certain criteria. Typically, RPP formulations fall into two categories: static and dynamic. The first assumes that access statistics are estimated in advance and remain static, and, therefore, a one-time replica distribution is sufficient (1RPP). In contrast, dynamic methods change the replicas in the network potentially upon every request. This paper proposes an alternative technique, named Continuous Replica Placement Problem (CRPP), which falls between the two extreme approaches. CRPP can be defined as: Given an already implemented replication scheme and estimated access statistics for the next time period, define a new replication scheme, subject to optimization criteria and constraints. As we show in the problem formulation, CRPP is different in that the existing heuristics in the literature cannot be used either statically or dynamically to solve the problem. In fact, even with the most careful design, their performance will be inferior since CRPP embeds a scheduling problem to facilitate the proposed mechanism. We provide insight on the intricacies of CRPP and propose various heuristics. Copyright 2005, ACM

On deploying tree structured agent applications in networked embedded systems

Given an application structured as a set of communicating mobile agents and a set of wireless nodes with sensing/actuating capabilities and agent hosting capacity constraints, the problem of deploying the application consists of placing all the agents on appropriate nodes without violating the constraints. This paper describes distributed algorithms that perform agent migrations until a "good" mapping is reached, the optimization target being the communication cost due to agent-level message exchanges. All algorithms are evaluated using simulation experiments and the most promising approaches are identified. © 2010 Springer-Verlag

Using multicast transfers in the replica migration problem: Formulation and scheduling heuristics

Performing replica migrations in the minimum possible time, also called the Replica Migration Problem (RMP), is crucial in distributed systems using replication. In this paper we tackle RMP when multicast transfers are available. We give a formal problem statement as a Mixed Integer Programming problem. It turns out that the problem is NP-hard. Therefore, we resolve to scheduling heuristics in order to find good solutions. Through simulations we identify different tradeoffs between performance and execution time and conclude on the most attractive approaches. © 2009 Springer

Agent placement in wireless embedded systems: Memory space and energy optimizations

Embedded applications can be structured in terms of mobile agents that are flexibly installed on available nodes. In wireless systems, such nodes typically have limited battery and memory resources; therefore it is important to place agents judiciously. In this paper we tackle the problem of placing a newcomer agent in such a system. The problem has two main components. First, enough memory space must be found or created at some node to place the agent. Second, the placement should be energy efficient. We present heuristics for tackling these two goals in a stepwise fashion, as well as a branch and bound method for achieving both goals at the same time. Our algorithms are centralized assuming a single entry point through which agents are injected into the system, with adequate knowledge of the system state and enough resources to run the proposed algorithms. The algorithms are evaluated under different simulated scenarios, and the tradeoffs across the two metrics (space, energy) are identified. © 2010 IEEE

Formal model and scheduling heuristics for the replica migration problem

Replication of the most popular objects is often used in distributed data provision systems to reduce access time and improve availability. In fact, a given replica placement scheme may have to be redefined as object popularity changes. Given two replica placement schemes X old and X new , the Replica Migration Problem (RMP) is to compute a schedule of replica transfers and deletions that lead from X old to X new in the shortest time possible. In this paper, we provide a rigorous problem formulation and prove that even for trivial cases RMP is intractable. We also propose a set of heuristics and evaluate them for different scenarios using simulations. © 2008 Springer-Verlag Berlin Heidelberg

Implementing replica placements: Feasibility and cost minimization

Given two replication schemes Xold and Xnew, the Replica Transfer Scheduling Problem (RTSP) aims at reaching Xnew, starting from Xold, with minimal implementation cost. In this paper we generalize the problem description to include special cases, where deadlocks can occur while in the process of implementing Xnew. We address this impediment by introducing artificial (dummy) transfers. We then prove that RTSP-decision is NP-complete and propose two kinds of heuristics. The first attempts to replace dummy transfers with valid ones, while the second minimizes the implementation cost. Experimental evaluation of the algorithms illustrates the merits of our approach. ©2007 IEEE

Implementation and Integration of Regional Health Care Data Networks in the Hellenic National Health Service

BACKGROUND: Modern health care is provided with close cooperation among many different institutions and professionals, using their specialized expertise in a common effort to deliver best-quality and, at the same time, cost-effective services. Within this context of the growing need for information exchange, the demand for realization of data networks interconnecting various health care institutions at a regional level, as well as a national level, has become a practical necessity. OBJECTIVES: To present the technical solution that is under consideration for implementing and interconnecting regional health care data networks in the Hellenic National Health System. METHODS: The most critical requirements for deploying such a regional health care data network were identified as: fast implementation, security, quality of service, availability, performance, and technical support. RESULTS: The solution proposed is the use of proper virtual private network technologies for implementing functionally-interconnected regional health care data networks. CONCLUSIONS: The regional health care data network is considered to be a critical infrastructure for further development and penetration of information and communication technologies in the Hellenic National Health System. Therefore, a technical approach was planned, in order to have a fast cost-effective implementation, conforming to certain specifications