Informatics Publishing Limited

B. Vidhyalakshmi ¹, R. S. Ponmagal ¹, J. M. Gnanasekar ¹

Affiliations
1 Department of Computer Science, Anna University of Technology, Tiruchirappalli, IN

Abstract

The motto of this paper is to analyze the performance of Service Oriented Sensor Network by utilizing Cloud technology. Cloud offers a way to share sensor information enhancing the performance of whole system. Wireless Sensor networks have become a vital part of many fields that involves remote sensing applications. The technical advancements are achieved at the cost of increased power consumptions of the sensors which will diminish the life-time of the sensors. The power of the sensors is spent by transmitting data continuously to the sink node. Moreover the autonomy of the system is considerably less. So, our intent is to develop an energy efficient architecture which is highly dynamic, flexible, scalable that provides an autonomous environment by making use of the Sensor Profiles as a placeholder. The concept is conceived based on identification of a particular sensor and data based on the Sensor Profile which is said to be unique for each and every sensor. The incorporated Cloud architecture in the proposed architecture ensures well managed data access and also provides an increased speed in data access. Obviously the deployment of Sensor Profile and sensed data in the Cloud enhances high degree of scalability and increased power efficiency. The Cloud SenPro architecture provides considerable pros such as rapid data access leading to quicker throughput and furthermore the architecture leads to an autonomous, power effective, dynamic, flexible and scalable environment.

Keywords

Sensor Profile, Cloud, XML and XSLT.

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J. M. Gnanasekar ¹, T. V. Anil Kumar ²

Affiliations
1 Department of Computer Science and Engineering, Anna University of Technology, Tiruchirappalli, Tamil Nadu, IN
2 Department, Anna University of Technology, Tiruchirappalli, Tamil Nadu, IN

Abstract

Mashup is a new application development approach that allows users to aggregate multiple services to create a service for a new purpose. Data and service mashup technology is getting more attention in both enterprise and academia for building new end users applications fast in the complex and heterogeneous network environment in relatively short periods of time with little or no additional costs to cover IT resources. Even if the Mashup approach opens new and broader opportunities for data/service consumers, the development process still requires the users to know not only how to write code using programming languages, but also how to select and use the different Web APIs from different services. Our architecture supports dynamic discovery of various APIs and performs interactive and sequential result refinement to improve the quality of the presented result. We proposed a script-based definition of mashups which facilitates the development as well as the dynamic execution of mashups. This architecture is realized using the QoS based Data and Service Mashup System (QDSMS), a novel platform to support end users to create, reuse and manage mashups based on mashup script based definition. We describe the overall design of QDSMS and discuss its main enabling technologies. This platform will improve the efficiency of mashup development and optimal use of storage and computing power of the network and server elements.

Keywords

Data and Service Mashups, Mashup Scripts, Mashup Platform, QoS.

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A. Kannaki ¹, J. M. Gnanasekar ²

Affiliations
1 Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, IN
2 Department of Computer Science and Engineering, Karpaga Vinayaga College of Engineering & Technology, IN

Abstract

Increasing demand for cloud computing is the reason for its ubiquitous growth in today's world. Enterprise consumers from large organization to small organization are preferring the services such as IaaS, SaaS and PaaS for their business growth with minimal cost because of on demand pay model. To employ such services for their organization, the cloud consumer and cloud service providers(CSP) has to consensus a agreement between them popularly known as Service Level Agreement(SLA). These SLA usually contains the type of service,Target Period, Quality of Service (QOS) properties, and Penalties called Service Level Objective (SLO) that has to be maintained during the service provision. This necessitates for the need to continuously monitor SLA violation to enforce penalties on the wronged one. Often this SLA management such as SLA monitoring and reporting is usually done by third party entity. But often these third party entities failed to ensure trust and compliance among the cloud consumers and CSPs. Henceforth in this paper, we propose a use of Intelligent Agent to monitor the SLO on behalf of the cloud consumers and report them of any discrepancies. We propose an Intelligent Agent Indemnification in SLA (IAIS) Architecture where the SLA management is entrusted to the dynamic, autonomous intelligent agent which is considered to be a substitute for human. We also measure some of the Key Performance Indicators and establish a threshold value to identify SLA violation based on threat threshold and will verify the same using simulation for effortless and efficient performance of the proposed framework.

Keywords

Cloud Service Providers (CSP), Service Level Agreement (SLA), Quality of Service (QOS), Service Level Objective (SLO), Intelligent Agent Indemnification in SLA (IAIS).

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M. Rajesh ¹, J. M. Gnanasekar ²

Affiliations
1 Department of Computer Science and Engineering, St. Peter's University, Chennai, IN
2 Department of Computer Science and Engineering, Karpaga Vinayaga College of Engineering and Technology, IN

Abstract

In most distributed systems, naming of nodes for low-level communication leverages topological location (such as node addresses) and is independent of any application. In this paper, we investigate an emerging class of distributed systems where low-level communication does not rely on network topological location. Rather, low-level communication is based on attributes that are external to the network topology and relevant to the application. When combined with dense deployment of nodes, this kind of named data enables in-network processing for data aggregation, collaborative signal processing, and similar problems. These approaches are essential for emerging applications such as sensor networks where resources such as bandwidth and energy are limited. This paper is the first description of the software architecture that supports named data and in-network processing in an operational, multi-application sensor-network. We show that approaches such as in-network aggregation and nested queries can significantly affect network traffic. In one experiment aggregation reduces traffic by up to 42% and nested queries reduce loss rates by 30%. Although aggregation has been previously studied in simulation, this paper demonstrates nested queries as another form of in-network processing, and it presents the first evaluation of these approaches over an operational testbed.

Keywords

Topological, Network Processing, Multi-Application.

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