Timeliness is one the most important factors in emergency management. Emergency notification mechanism has to be hassle free and quick, in order to have efficient response for any disaster, health-fix, act of terrorism, etc. In this paper, we present service architecture for emergency alert, using Fog computing. Fog computing brings cloud resources close to the underlying devices and IoTs, which makes it ideal for latency sensitive services. Furthermore, Fog is used for offloading resource constrained devices. Our smart phone based service, known as Emergency Help Alert Mobile Cloud (E-HAMC) provides a quick way of notifying the relevant emergency dealing department, utilizing the services of Fog for offloading as well as pre-processing purposes. The service sends the location of incident and contacts the appropriate emergency dealing department automatically through already stored contact numbers. The emergency related information is then synchronized automatically from Fog to the Cloud, allowing further analysis and improvement in safety of the people and creates extended portfolio of services for the concerned authorities as well as the users. Performance in most certain scenarios is also evaluated and presented in this study, which shows the applicability of our system and its future prospects.

E-HAMC: Leveraging Fog computing for emergency alert service

As technology develops, more human-made devices are able to make use of Internet to communicate with each other, thus enabling the Internet of Things (IoT) era to emerge. The amount of data IoT entities generate can overwhelm computer infrastructures not prepared for such data deluge and consequent need for more CPU power. Cloud computing offers a solution at infrastructure level that alleviates such a problem by offering highly scalable computing platforms that can be configured on demand to meet constant changes of applications requirements in a pay-per-use mode. Current approaches enabling IoT applications are domain-specific or focus only on interaction with sensors, thus they cannot be easily ported to other domains nor provide means of interactions with data sources other than sensors. To address this issue, in this paper we introduce a data-centric framework for development of IoT applications executed in clouds. The framework handles connection to data sources, data filtering, and utilization of cloud resources including provisioning, load balancing, and scheduling, enabling developers to focus on the application logic and therefore facilitating the development of IoT applications. We present a prototype application executing on AWS, built on top of the Aneka Cloud Application Platform and present experiments demonstrating the use of our framework for building an application capable of processing input from different sources and analysing them using easy-to-use APIs provided by Aneka.

A data-centric framework for development and deployment of Internet of Things applications in clouds

The Cloud Computing and Services Science book comprises a collection of the best papers presented at the International Conference on Cloud Computing and Services Science (CLOSER), which was held in The Netherlands in May 2011. In netting papers from the conference researchers and experts from all over the world explore a wide-ranging variety of the emerging Cloud Computing platforms, models, applications and enabling technologies. Further, in several papers the authors exemplify essential links to Services Science as service development abstraction, service innovation, and service engineering, acknowledging the service-orientation in most current IT-driven structures in the Cloud. The Cloud Computing and Services Science book is organized around important dimensions of technology trends in the domain of cloud computing in relation to a broad scientific understanding of modern services emerging from services science. The papers of this book are inspired by scholarly and practical work on the latest advances related to cloud infrastructure, operations, security, services, and management through the global network. This book includes several features that will be helpful, interesting, and inspirational to students, researchers as well as practitioners. Professionals and decision makers working in this field will also benefit from this book

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Cloud Computing and Services Science

Cloud computing is the latest technology to provide resources from the large data centers. Cloud Computing is made available as a service to the users. Many web applications can get benefit from automatic scaling property of cloud where the no of resources utilization can be scale up and down automatically by cloud service provider. So here present system that provides automatic scaling for internet application in cloud environment. So every application instance encapsulated into the virtual machine and model it as the Class Constraint Bin Packing (CCBP) problem, where each class represents an application and each server is a bin and make use of virtualization technology for fault isolation. Now many business customers require good satisfy response services from cloud. So design and develop semi online color set algorithm that attain good demand satisfaction ratio and also when load becomes low it reducing number of server and save energy. It take help of green computing to adjusting the placement of application instance adaptively and putting ideal machine into the standby mode. Cloud computing is a paradigm that based on sharing data and computations over a scalable network of nodes, spanning across end user computers, data centers and web services. A scalable network of such nodes form a cloud. An application based on these clouds is considered as a cloud application. In recent years, most of the software, hardware and networking have extended, specially service-based cloud computing has changed the traditional computer and its centralized storage. This cloud model raise availability and is composed of five essential characteristics ,three delivery models, and four deployment models . Even though the cloud computing model is sometimes advocated as providing infinite capacity on demand, the capacity of data centers in the real world is finite. The illusion of infinite capacity in the cloud is provided through statistical multiplexing. When a large number of applications experience their peak demand around the same time, the available resources in the cloud can become constrained and some of the demand may not be satisfied. We define the demand satisfaction ratio as the percentage of application demand that is satisfied successfully. The total computing capacity available to an application is limited by the placement of its running instances on the servers. The more instances an application has and the more powerful the underlying servers are, the higher the potential capacity for fulfilling the application demand. On the other hand, when the demand of the applications is low, it is important to preserve energy by reducing the number of servers used. Various studies have found that the cost of electricity is a prime portion of the operation cost of large data centers. At the same time, the average server usage in many Internet data centers is very low.

Automatic scaling of internet applications for cloud computing services

Dedicated and expensive computing platforms are commonly applied to mobile network systems. This is necessary, despite the economic burden, due to strict performance requirements in availability, latency and throughput. However, cloud computing is changing the rules of the game by offering cost efficient and high performance computer systems. Pay-per-use principle is helping network administrators to scale the computing capacity on a need basis, reducing both capex and opex costs. Several networks can benefit from this advantage in wireless services, including both end user and internal back end services. The focus in this paper is on the Short Message Service (SMS), which is one of the most successful and widespread end user services after voice in mobile networks. The SMS Center (SMSC) is used as a test bed to optimize the usage of public and private clouds in network operations, both in technology and business. This paper presents a hybrid cloud architecture that enables an automatic up-and-down-scaling of the system, using dynamic resource provisioning and depending on the service load. In addition, a cost analysis to find the optimal balance between public and private clouds is described. Finally, the proposed solution is thoroughly evaluated, future research ideas are highlighted and conclusions are drawn.

Hybrid cloud architecture for short message services

The fixed-line and mobile telephony network is one of the crucial elements of an emergency response to a disaster event. However, frequently the phone network is overwhelmed in such situations and is disrupted. It is not cost-effective to maintain an over-provisioned IT infrastructure for such rare events. Cloud computing allows users to create resources on-demand and can enable an IT infrastructure that scales in response to the demands of disaster management. In this paper, we introduce a system that uses the Amazon EC2 service to automatically scale up a software telephony network in response to a large volume of calls and scale down in normal times. We demonstrate the efficacy of this system through experiments based on real-world data.

Ray

Papers

Auto-scaling emergency call centres using cloud resources to handle disasters