An Adaptive Multi Agent Service Discovery for Peer to Peer Cloud Services

Author(s):  
Moses Olaifa ◽  
Sunday Ojo ◽  
Tranos Zuva
Author(s):  
Gitosree Khan ◽  
Anirban Sarkar ◽  
Sabnam Sengupta

Enterprise cloud bus (ECBS) is a multi-agent-based abstraction layer framework, responsible for publishing and discovery of services in an Inter-cloud environment. Our work focuses on the service discovery model (HBSD) using Hadoop that leads to the challenges of automatic web service discovery patterns. It has been observed that the RDBMS can handle only data sizes up to a few Terabytes but fails to scale beyond that, so Apache Hadoop can be used for parallel processing of massive datasets. This article provides a novel Hadoop based Service Discovery (HBSD) approach that can handle vast amount of datasets generated from heterogeneous cloud services. The novelty of the proposed architecture coordinates cloud participants, automate service registration pattern, reconfigure discover services and focus on aggregating heterogeneous services from Inter-cloud environments. Moreover, this particle states a novel and efficient algorithm (HBSDMCA) for finding the appropriate service as per user's requirements that can provide higher QoS to the user request for web services.


2012 ◽  
Vol 10 ◽  
pp. 976-983 ◽  
Author(s):  
Stefan D. Bruda ◽  
Farzad Salehi ◽  
Yasir Malik ◽  
Bessam Abdulrazak

2012 ◽  
Vol 28 (7) ◽  
pp. 1090-1099 ◽  
Author(s):  
Neeraj Kumar ◽  
Rahat Iqbal ◽  
Naveen Chilamkurti

Computing ◽  
2010 ◽  
Vol 91 (2) ◽  
pp. 169-215 ◽  
Author(s):  
Jordi Campos ◽  
Marc Esteva ◽  
Maite López-Sánchez ◽  
Javier Morales ◽  
Maria Salamó

2012 ◽  
pp. 232-259
Author(s):  
Eddy Caron ◽  
Frédéric Desprez ◽  
Franck Petit ◽  
Cédric Tedeschi

Within distributed computing platforms, some computing abilities (or services) are offered to clients. To build dynamic applications using such services as basic blocks, a critical prerequisite is to discover those services. Traditional approaches to the service discovery problem have historically relied upon centralized solutions, unable to scale well in large unreliable platforms. In this chapter, we will first give an overview of the state of the art of service discovery solutions based on peer-to-peer (P2P) technologies that allow such a functionality to remain efficient at large scale. We then focus on one of these approaches: the Distributed Lexicographic Placement Table (DLPT) architecture, that provide particular mechanisms for load balancing and fault-tolerance. This solution centers around three key points. First, it calls upon an indexing system structured as a prefix tree, allowing multi-attribute range queries. Second, it allows the mapping of such structures onto heterogeneous and dynamic networks and proposes some load balancing heuristics for it. Third, as our target platform is dynamic and unreliable, we describe its powerful fault-tolerance mechanisms, based on self-stabilization. Finally, we present the software prototype of this architecture and its early experiments.


Author(s):  
Brahmananda Sapkota ◽  
Laurentiu Vasiliu ◽  
Ioan Toma ◽  
Dumitru Roman ◽  
Chris Bussler

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