With the advent of Grid technologies, scientists and engineers are building complex and sophisticated applications to manage and process large data sets, and execute scientific experiments on distributed Grid resources [33]. Building complex workflows requires means for composing and executing distributed applications. A workflow expresses an automation of procedures wherein files and data are passed between procedures applications according to a defined set of rules, to achieve an overall goal [13]. A workflow management system defines, manages and executes workflows on computing resources. The use of the workflow paradigm for application composition on Grids offers several advantages [22] such as: • Ability to build dynamic applications and orchestrate the use of distributed resources. • Utilization of resources that are located in a suitable domain to increase throughput or reduce execution costs. • Execution spanning multiple administrative domains to obtain specific processing capabilities. • Integration of multiple teams involved in managing different parts of the experiment workflow – thus promoting inter-organizational collaborations.
HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. WISDOM: A Grid-Enabled Drug Discovery Initiative Against Malaria Vincent Breton, D. Kim, G. Rastelli
Process migration refers to the act of transferring a process in the middle of its execution from one machine to another in a network.In this paper, we proposed a process migration framework for Linux OS.It is a multilayer architecture to confine every functionality independent section of the system in separate layer.This architecture is capable of supporting diverse applications due to generic user space interface and dynamic structure that can be modified according to demands.
Nowadays the number of available processing cores within computing nodes which are used in recent clustered environments, are growing up with a rapid rate.Despite this trend, the number of available network interfaces in such computing nodes has almost been remained unchanged.This issue can lead to high usage of network interface in many workloads, especially in heavy-communicating workloads.As a result, network interface may raise as a performance bottleneck and can drastically degrade the performance.The goal of this paper is to introduce a new process mapping strategy in multi-core clusters aimed at reducing network interface contention and improving inter-node communication performance of parallel applications.Performance evaluation of the new mapping algorithm in synthetic and real workloads indicates that the new strategy can achieve 5% to 90% performance improvement in heavy communicating workloads, compared to other well-known methods.
Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality.Grid applications typically deal with large amounts of data.In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication.In this paper we present a new mechanism for distributed and big data storage and resource discovery services.Here we proposed an architecture named Dynamic and Scalable Storage Management (DSSM) architecture in grid environments.This allows in grid computing not only sharing the computational cycles, but also share the storage space.The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications.The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used.The DSSM divides all Grid Oriented Storage devices (nodes) into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management.Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows.To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results.Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.
Grid computing or computational grid is always a vast research field in academic, as well as in industry also. Computational grid provides resource sharing through multi-institutional virtual organizations for dynamic problem solving. Various heterogeneous resources of different administrative domain are virtually distributed through different network in computational grids. Thus any type of failure can occur at any point of time and job running in grid environment might fail. Hence fault tolerance is an important and challenging issue in grid computing as the dependability of individual grid resources may not be guaranteed. In order to make computational grids more effective and reliable fault tolerant system is necessary. The objective of this paper is to review different existing fault tolerance techniques applicable in grid computing. This paper presents state of the art of various fault tolerance technique and comparative study of the existing algorithms.
In order to effectively analyze or evaluate the performance of Wireless Local Area Networks (WLANs), it is important to identify what types of network settings can cause bad performance in the network when analyzing poor network performance, there is an important factor which is responsible for poor performance is when a number of users may obtain a much larger share of the available bandwidth in access point in a limited boundary as provided in the concept of cell breathing technique. In this paper, we proposed a new concept in which we can set bandwidth limitation so that no user can access data more than the specified limit for a particular access point. In this way the different users will get an efficient access over the network.
Grid computing solves the increasing need of scientific, engineering and research problems.It combines the geographically distributed resources to solve a computation intensive problem which cannot be solved using a single resource.Resource sharing requires more optimized algorithmic structure, otherwise the response time is increased and the resource utilization is reduced.In order to avoid such reduction in the performance of the grid system, an optimal resource sharing algorithm is required.The ACO solves many engineering problems and provides optimal result which includes Travelling Salesman Problem, Network Routing, and Scheduling.This paper proposes Load Shared Ant Colony Optimization (LSACO) which shares the load among the available resources.The proposed method considers memory requirement as a parameter to distribute the load among Grid resources.LSACO reduces the overall response time and increases the resource utilization and number of tasks scheduled.The proposed method has been tested for different types of tasks and resources.
In this paper we present a dynamic network traffic balancing approach using strong migration on an agent based grid environment. The paper focuses on three different areas, namely load balancing, strong mobility and CSP (Constraint Satisfaction Problem) approach. We use CSP approach for making task migration decisions. Strong task migration is used to move tasks between nodes at runtime to maintain dynamic balancing. Our approach is implemented on an agent based grid system, where all loads can be formulated as weighted constraints of a CSP. We define inter-messaging rates of tasks as the main load of our system. Activated by the results produced by CSP execution, the strong migration mechanism we have integrated into the grid system maintains dynamic traffic balancing by transferring tasks such that frequently communicating tasks end up on the same node and do not consume network bandwidth. Experimental results show remarkable reduction on network use of the grid system.
Recent advances in mobile computing, and strong interest of the scientific community in the Grid have led to research into the Mobile Grid.One primary issue associated with the efficient and effective utilization of mobile resources in a mobile grid is scheduling of tasks.In this paper, a task scheduling algorithm is proposed based on the dynamic prediction of resource mobility and battery power in the mobile grid environment.The mobility is predicted based on the movement type, movement pattern and movement direction of the mobile resource within the zone.The battery power is predicted based the C-rate of the mobile resource.The availability prediction of a mobile resource is evaluated during the task submission and this allows the system to consider run-time parameters prior to execution.The evaluation study employs a number of experiments with various simulation settings.The simulation results point to the efficacy of the proposed work.
Grid computing enlarge with computing platform which is collection of heterogeneous computing resources connected by a network across dynamic and geographically dispersed organization to form a distributed high performance computing infrastructure. Grid computing solves the complex computing problems amongst multiple machines. Grid computing solves the large scale computational demands in a high performance computing environment. The main emphasis in the grid computing is given to the resource management and the job scheduler .The goal of the job scheduler is to maximize the resource utilization and minimize the processing time of the jobs. Existing approaches of Grid scheduling doesn’t give much emphasis on the performance of a Grid scheduler in processing time parameter. Schedulers allocate resources to the jobs to be executed using the First come First serve algorithm. In this paper, we have provided an optimize algorithm to queue of the scheduler using various scheduling methods like Shortest Job First, First in First out, Round robin. The job scheduling system is responsible to select best suitable machines in a grid for user jobs. The management and scheduling system generates job schedules for each machine in the grid by taking static restrictions and dynamic parameters of jobs and machines into consideration. The main purpose of this paper is to develop an efficient job scheduling algorithm to maximize the resource utilization and minimize processing time of the jobs. Queues can be optimized by using various scheduling algorithms depending upon the performance criteria to be improved e.g. response time, throughput. The work has been done in MATLAB using the parallel computing toolbox.
Grid computing is a collection of distributed resources interconnected by networks to provide a unified virtual computing resource view to the user. Grid computing has one important responsibility of resource management and techniques to allow the user to make optimal use of the job completion time and achieving good throughput. It is a big deal to design the efficient scheduler and is implementation. In this paper, the constraint based job and resource scheduling algorithm has been proposed. The four constraints are taken into account for grouping the jobs, i.e. Resource memory, Job memory, Job MI and the fourth constraint L2 cache are considered. Our implementation is to reduce the processing time efficiently by adding the fourth constraint L2 cache of the resource and is allocated to the resource for parallel computing. The L2 cache is a part of computer’s processor; it increases the performance of computer. It is smaller and extremely fast computer memory. The use of more constraint of the resource and job can increase the efficiency more. The work has been done in MATLAB using the parallel computing toolbox. All the constraints are calculated using different functions in MATLAB and are allocated to the resource based on it. The resource memory, Cache, job memory size and job MI are the key factors to group the jobs according to the available capability of the selected resource. The processing time is taken into account to analyze the feasibility of the algorithms.
The adaptability in software is the main fascinating concern for which most of the software architects today are really interested in providing the Autonomic computing. In order to provide remedy for the service failures that occurs at the servers of the respective service providers, there is a need to introduce the self-reconfiguration planes to be applied astronomically without the interruption of the administrator to solve the problem manually. Different programming models have been introduced for providing the dynamic behavior of the services being provided. Few among them are the Aspect Oriented Programming (AOP) and Feature Oriented Programming (FOP) both of them having the ability to modularize the crosscutting concerns, where the former is dependent on aspects, advice and lateral one on the collaboration design and refinements. In this paper we will use the design patterns which will satisfy the properties of autonomic computing system: for the Decision-Making phase we will introduce Case-Based Reasoning design pattern, and for Reconfiguration phase we will introduce Reactor design pattern. The most important proposal in our design pattern is that we will use the Association Rule Learning method of Data Mining to learn about new services that can be added along with the requested service to make the service as a dynamic composition of two or more services. Then we will include the new service as an aspectual feature module code without interrupting the user. The pattern is described using a java-like notation for the classes and interfaces. A simple UML and Sequence diagram are depicted.
With the increasing development of high-speed wide-area networks and powerful though low cost computational resources, grid computing has emerged as an attractive computing paradigm.With recent advances in computing, the scope of grid computing has been expanded to include mobile and pervasive devices. Grids have become one of the highest consumers of energy. High performance computing is achieved at the cost of energy consumption. Increasing the performance of computer systems requires increasing number of resources which leads to higher power consumption and it creates negative impact on environment. Idle sites in grid are direct sources of energy waste. Saving energy causes two direct advantages: financial and environmental cost reduction and sustainability. With the Grid becoming a viable high-performance alternative to the traditional supercomputing environment, various aspects of Grid resource utilization which can help in energy conservation are gaining significance. In this paper we explore the possibility of reduction in energy consumption of a grid of heterogeneous computers by making use of different power states of cpu.
This paper describes the background of smart information infrastructure and the needs for smart grid information security. It introduces the conceptual analysis to the methodology with the application of hermeneutic circle and information security functional requirement identification. Information security for the grid market cover matters includes automation and communications industry that affects the operation of electric power systems and the functioning of the utilities that manage them and its awareness of this information infrastructure has become critical to the reliability of the power system. Community benefits from of cost savings, flexibility and deployment along with the establishment of wireless communications. However, concern revolves around the security protections for easily accessible devices such as the smart meter and the related communications hardware. On the other hand, the changing points between traditional versus smart grid networking trend and the information security importance on the communication field reflects the criticality of grid information security functional requirement identification. The goal of this paper is to identify the functional requirement and relate its significance addresses to the consumer requirement of an information security of a smart grid. Vulnerabilities may bring forth possibility for an attacker to penetrate a network, make headway admission to control software, alter it to load conditions that destabilize the grid in unpredictable ways. Focusing on the grid information security functional requirement is stepping ahead in developing consumer trust and satisfaction toward smart grid completeness.
This paper is designed to introduce the reader to the fundamental information for future or next Generation Technology .Forth Generation system implement in few countries & 4G systems is still a predominantly research and development and make an overview of next generation system i.e.5G communication. In this Paper presents an overview of the fifth generation mobile networks with emphasis on current and future trends in the areas of wireless networking, multimedia technology, network architecture, and network services. Related research in the development of future mobile systems has been highlighted. Beginning with prognoses of 5G Communication, architecture model of wireless communication & comparison with all the generation technology.
Many energy-aware routing protocols have been proposed for wireless sensor networks. Most of them are only energy savers and do not take care about energy balancing. The energy saver protocols try to decrease the energy consumption of the network as a whole; however the energy manager protocols balance the energy consumption in the network to avoid network partitioning. This means that energy saver protocols are not necessarily energy balancing and vice versa. However, the lifetime of wireless sensor network is strictly depending on energy consumption; therefore, energy management is an essential task to be considered. This paper proposes an energy aware routing protocol, named FEAR, which considers energy balancing and energy saving. It finds a fair trade-off between energy balancing and energy saving by fuzzy set concept. FEAR routing protocol is simulated and evaluated by Glomosim simulator.
With the increasing popularity of Internet-based services and applications, power efficiency is becoming a major concern for data center operators, as high electricity consumption not only increases greenhouse gas emissions, but also increases the cost of running the server farm itself.In this paper we address the problem of maximizing the revenue of a service provider by means of dynamic allocation policies that run the minimum amount of servers necessary to meet user's requirements in terms of performance.The results of several experiments executed using Wikipedia traces are described, showing that the proposed schemes work well, even if the workload is non-stationary.Since any resource allocation policy requires the use of forecasting mechanisms, various schemes allowing compensating errors in the load forecasts are presented and evaluated.
This paper is an empirical case study to predict or estimate the performance and variability of same type software frameworks used for web application development. First we explore and analyze (Web Applications) PHP and ASP.NET considering quality attributes. Second we develop two same web applications i.e. Online Book’s Mart (Web applications to purchase books online) in PHP and ASP.NET. Finally we conduct automated testing to determine and analyze application’s performance. Software architecture, CSS, database design, database constraints were tried to keep simple and same for both applications i.e. Applications developed in PHP and ASP.NET. This similarity helps to establish realistic comparison of applications performance and variability. The application’s performance and variability is measured with help of automated scripts.
Testing process is to detect variance between actual and expected results, to make good quality software. Testing is necessary but to test each and every part of software is not feasible. There should be threshold point to stop testing, in this paper we proposed an analytical scheme which provides threshold values to stop testing without compromising the quality of software. By using proposed scheme, developer can easily find out sufficient and enough level of testing.
