Load balancing in distributed query management at web enabled systems

Every day more and more Business are using web as compulsory medium to provide services. Ever increase in technological advancement leads more devices and applications are accessing web based application around the clock. So single node web applications are prone collapse, designing an application with Distributed frame work and mange those application often reduce the risk of single point failure. In that strategy load balancers plays an important role to direct the traffic to multiple Servers. Existing load balancers are Prone to fail and centralized strategy to distribute the load among the server. Our proposed heuristic based load balancer follows Decentralized approach to solve the problem and our ANN based supervised back propagation technique gives optimized results that existing Load balancer

Towards Autonomic Service Provisioning Systems

This paper discusses our experience in building SPIRE, an autonomic system for service provision. The architecture consists of a set of hosted Web Services subject to QoS constraints, and a certain number of servers used to run session-based traffic. Customers pay for having their jobs run, but require in turn certain quality guarantees: there are different SLAs specifying charges for running jobs and penalties for failing to meet promised performance metrics. The system is driven by an utility function, aiming at optimizing the average earned revenue per unit time. Demand and performance statistics are collected, while traffic parameters are estimated in order to make dynamic decisions concerning server allocation and admission control. Different utility functions are introduced and a number of experiments aiming at testing their performance are discussed. Results show that revenues can be dramatically improved by imposing suitable conditions for accepting incoming traffic; the proposed system performs well under different traffic settings, and it successfully adapts to changes in the operating environment.Comment: 11 pages, 9 Figures, http://www.wipo.int/pctdb/en/wo.jsp?WO=201002636

An index based load balancer to enhance transactional application servers' QoS

The Web is the preferred interface for the new generation of applications. Web services are an ubiquitous concept for both, developers and managers. These Web applications require distribution systems of web requests that allow and support the dynamism of these environments, to provide service availability and resource usage, commonly heterogeneous. Web services provide an entry point to the Web application business logic. Therefore, the design of appropriate load balancing strategies, taking into account the dynamic nature of the application servers' activity, is essential. In this work we present a load balancing policy and its integration inbetween static and dynamic layers of any web application that uses application servers. The strategy gets the status report of each application server, used to later distribute web requests. Results that show how the strategy succeed are presented

Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud

With the advent of cloud computing, organizations are nowadays able to react rapidly to changing demands for computational resources. Not only individual applications can be hosted on virtual cloud infrastructures, but also complete business processes. This allows the realization of so-called elastic processes, i.e., processes which are carried out using elastic cloud resources. Despite the manifold benefits of elastic processes, there is still a lack of solutions supporting them. In this paper, we identify the state of the art of elastic Business Process Management with a focus on infrastructural challenges. We conceptualize an architecture for an elastic Business Process Management System and discuss existing work on scheduling, resource allocation, monitoring, decentralized coordination, and state management for elastic processes. Furthermore, we present two representative elastic Business Process Management Systems which are intended to counter these challenges. Based on our findings, we identify open issues and outline possible research directions for the realization of elastic processes and elastic Business Process Management.Comment: Please cite as: S. Schulte, C. Janiesch, S. Venugopal, I. Weber, and P. Hoenisch (2015). Elastic Business Process Management: State of the Art and Open Challenges for BPM in the Cloud. Future Generation Computer Systems, Volume NN, Number N, NN-NN., http://dx.doi.org/10.1016/j.future.2014.09.00

StreamCloud: An elastic and scalable data streaming system

Many applications in several domains such as telecommunications, network security, large scale sensor networks, require online processing of continuous data lows. They produce very high loads that requires aggregating the processing capacity of many nodes. Current Stream Processing Engines do not scale with the input load due to single-node bottlenecks. Additionally, they are based on static con?gurations that lead to either under or over-provisioning. In this paper, we present StreamCloud, a scalable and elastic stream processing engine for processing large data stream volumes. StreamCloud uses a novel parallelization technique that splits queries into subqueries that are allocated to independent sets of nodes in a way that minimizes the distribution overhead. Its elastic protocols exhibit low intrusiveness, enabling effective adjustment of resources to the incoming load. Elasticity is combined with dynamic load balancing to minimize the computational resources used. The paper presents the system design, implementation and a thorough evaluation of the scalability and elasticity of the fully implemented system

Understanding and Hardening Blockchain Network Security Against Denial of Service Attacks

This thesis aims to examine the security of a blockchain\u27s communication network. A blockchain relies on a communication network to deliver transactions. Understanding and hardening the security of the communication network against Denial-of-Service (DoS) attacks are thus critical to the well-being of blockchain participants. Existing research has examined blockchain system security in various system components, including mining incentives, consensus protocols, and applications such as smart contracts. However, the security of a blockchain\u27s communication network remains understudied. In practice, a blockchain\u27s communication network typically consists of three services: RPC service, P2P network, and mempool. This thesis examines each service\u27s designs and implementations, discovers vulnerabilities that lead to DoS attacks, and uncovers the P2P network topology. Through systematic evaluations and measurements, the thesis confirms that real-world network services in Ethereum are vulnerable to DoS attacks, leading to a potential collapse of the Ethereum ecosystem. Besides, the uncovered P2P network topology in Ethereum mainnet suggests that critical nodes adopt a biased neighbor selection strategy in the mainnet. Finally, to fix the discovered vulnerabilities, practical mitigation solutions are proposed in this thesis to harden the security of Ethereum\u27s communication network

Applying Graph Partitioning Methods in Measurement-based Dynamic Load Balancing

Load imbalance in an application can lead to degradation of performance and a significant drop in system utilization. Achieving the best parallel efficiency for a program requires optimal load balancing which is an NP-hard problem. This paper explores the use of graph partitioning algorithms, traditionally used for partitioning physical domains/meshes, for measurement-based dynamic load balancing of parallel applica- tions. In particular, we present repartitioning methods that consider the previous mapping to minimize dynamic migration costs. We also discuss the use of a greedy algorithm in conjunction with iterative graph partitioning algorithms to reduce the load imbalance for graphs with heavily skewed load distributions. These algorithms are implemented in a graph partitioning toolbox called SCOTCH and we use CHARM++, a migratable objects based programming model, to experiment with various load balancing scenarios. To compare with different load balancing strategies based on graph partitioners, we have implemented METIS and ZOLTAN-based load balancers in CHARM++. We demonstrate the effectiveness of the new algorithms de- veloped in SCOTCH in the context of the NAS BT solver and two micro-benchmarks. We show that SCOTCH based strategies lead to better performance compared to other existing partitioners, both in terms of the application execution time and fewer number of objects migrated.Ope

Runtime support for load balancing of parallel adaptive and irregular applications

Applications critical to today\u27s engineering research often must make use of the increased memory and processing power of a parallel machine. While advances in architecture design are leading to more and more powerful parallel systems, the software tools needed to realize their full potential are in a much less advanced state. In particular, efficient, robust, and high-performance runtime support software is critical in the area of dynamic load balancing. While the load balancing of loosely synchronous codes, such as field solvers, has been studied extensively for the past 15 years, there exists a class of problems, known as asynchronous and highly adaptive , for which the dynamic load balancing problem remains open. as we discuss, characteristics of this class of problems render compile-time or static analysis of little benefit, and complicate the dynamic load balancing task immensely.;We make two contributions to this area of research. The first is the design and development of a runtime software toolkit, known as the Parallel Runtime Environment for Multi-computer Applications, or PREMA, which provides interprocessor communication, a global namespace, a framework for the implementation of customized scheduling policies, and several such policies which are prevalent in the load balancing literature. The PREMA system is designed to support coarse-grained domain decompositions with the goals of portability, flexibility, and maintainability in mind, so that developers will quickly feel comfortable incorporating it into existing codes and developing new codes which make use of its functionality. We demonstrate that the programming model and implementation are efficient and lead to the development of robust and high-performance applications.;Our second contribution is in the area of performance modeling. In order to make the most effective use of the PREMA runtime software, certain parameters governing its execution must be set off-line. Optimal values for these parameters may be determined through repeated executions of the target application; however, this is not always possible, particularly in large-scale environments and long-running applications. We present an analytic model that allows the user to quickly and inexpensively predict application performance and fine-tune applications built on the PREMA platform

Branch and Bound Based Load Balancing for Parallel Applications

Abstract. Many parallel applications are highly dynamic in nature. In some, computation and communication patterns change gradually dur-ing the run; in others those characteristics change abruptly. Such dy-namic applications require an adaptive load balancing strategy. We are exploring an adaptive approach based on multi-partition object-based decomposition, supported by object migration. For many applications, relatively infrequent load balancing is needed. In these cases it becomes economical to spend considerable computation time toward arriving at a nearly optimal mapping of objects to processors. We present an optimal-seeking branch and bound based strategy that finds nearly optimal so-lutions to such load balancing problems quickly, and can continuously improve such solutions as time permits.