A performance study of routing protocols for mobile grid environment

Integration of mobile wireless consumer devices into the Grid initially seems unlikely due to limitation such as CPU performance,small secondary storage, heightened battery consumption sensitivity and unreliable low-bandwidth communication. The current grid architecture and algorithm also do not take into account the mobile computing environment since mobile devices have not been seriously considered as valid computing resources or interfaces in grid communities. This paper presents the results of simulation done in identifying a suitable ad hoc routing protocol that can be used for the target grid application in mobile environment. The simulation comparing three ad hoc routing protocols named DSDV, DSR and AODV

Simulation Analysis of New 802.11KT MAC Protocol And IEEE 802.11 MAC Protocol for Grid Topology in MANET Using NS-2

This paper compare the performance analysis of newly designed 802.11KT MAC protocol for a mobile ad-hoc network (MANET) communication system which aims to provide low cost, small end to end delay and more throughputs with the existing IEEE 802.11 MAC protocol. Simulation is the main method for evaluating the performance of protocol. It is subjected to comparison of performance of existing IEEE802.11 Mac protocol and new 802.11KT Mac protocol for random topology in MANET. The Adhoc On Demand Distance Vector (AODV) is used as routing protocol with NS-2 simulator. Simulation results indicated that newly designed 802.11KT MAC protocol has better performance than existing IEEE 802.11 MAC protocol

Proof-of-Concept Application - Annual Report Year 1

In this document the Cat-COVITE Application for use in the CATNETS Project is introduced and motivated. Furthermore an introduction to the catallactic middleware and Web Services Agreement (WS-Agreement) concepts is given as a basis for the future work. Requirements for the application of Cat-COVITE with in catallactic systems are analysed. Finally the integration of the Cat-COVITE application and the catallactic middleware is described. --Grid Computing

It's about THYME: On the design and implementation of a time-aware reactive storage system for pervasive edge computing environments

This work was partially supported by Fundacao para a Ciencia e a Tecnologia (FCT-MCTES) through project DeDuCe (PTDC/CCI-COM/32166/2017), NOVA LINCS UIDB/04516/2020, and grant SFRH/BD/99486/2014; and by the European Union through project LightKone (grant agreement n. 732505).Nowadays, smart mobile devices generate huge amounts of data in all sorts of gatherings. Much of that data has localized and ephemeral interest, but can be of great use if shared among co-located devices. However, mobile devices often experience poor connectivity, leading to availability issues if application storage and logic are fully delegated to a remote cloud infrastructure. In turn, the edge computing paradigm pushes computations and storage beyond the data center, closer to end-user devices where data is generated and consumed, enabling the execution of certain components of edge-enabled systems directly and cooperatively on edge devices. In this article, we address the challenge of supporting reliable and efficient data storage and dissemination among co-located wireless mobile devices without resorting to centralized services or network infrastructures. We propose THYME, a novel time-aware reactive data storage system for pervasive edge computing environments, that exploits synergies between the storage substrate and the publish/subscribe paradigm. We present the design of THYME and elaborate a three-fold evaluation, through an analytical study, and both simulation and real world experimentations, characterizing the scenarios best suited for its use. The evaluation shows that THYME allows the notification and retrieval of relevant data with low overhead and latency, and also with low energy consumption, proving to be a practical solution in a variety of situations.publishersversionpublishe

Proximity-based systems: Incorporating mobility and scalability through proximity sensing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.This thesis argues that the concept of spatial proximity offers a viable and practical option for the development of context-aware systems for highly mobile and dynamic environments. Such systems would overcome the shortcomings experienced by today’s location-based and infrastructure dependent systems whose ability to deliver context-awareness is prescribed by their infrastructure. The proposed architecture will also allow for scalable interaction as against the single level of interaction in existing systems which limits services to a particular sized area. The thesis examines the concept of spatial proximity and demonstrates how this concept can be exploited to take advantage of technological convergence to offer mobility and scalability to systems. It discusses the design of a proximity-based system that can deliver scalable context-aware services in highly mobile and dynamic environments. It explores the practical application of this novel design in a proximity-sensitive messaging application by creating a proof-of-concept prototype. The proof-of-concept prototype is used to evaluate the design as well as to elicit user views and expectations about a proximity-based approach. Together these provide a valuable insight into the applicability of the proximity-based approach for designing context-aware systems. The design and development work discussed in the thesis presents a Proximity-Sensitive System Architecture that can be adapted for a variety of proximity-sensitive services. This is illustrated by means of examples, including a variety of context-aware messaging applications. The thesis also raises issues for information delivery, resource sharing, and human-computer interaction. While the technological solution (proximity-based messaging) offered is only one among several that can be developed using this architecture, it offers the opportunity to stimulate ideas in the relatively new field of proximity and technological convergence research, and contributes to a better understanding of their potential role in offering context-aware services

A critical analysis of research potential, challenges and future directives in industrial wireless sensor networks

In recent years, Industrial Wireless Sensor Networks (IWSNs) have emerged as an important research theme with applications spanning a wide range of industries including automation, monitoring, process control, feedback systems and automotive. Wide scope of IWSNs applications ranging from small production units, large oil and gas industries to nuclear fission control, enables a fast-paced research in this field. Though IWSNs offer advantages of low cost, flexibility, scalability, self-healing, easy deployment and reformation, yet they pose certain limitations on available potential and introduce challenges on multiple fronts due to their susceptibility to highly complex and uncertain industrial environments. In this paper a detailed discussion on design objectives, challenges and solutions, for IWSNs, are presented. A careful evaluation of industrial systems, deadlines and possible hazards in industrial atmosphere are discussed. The paper also presents a thorough review of the existing standards and industrial protocols and gives a critical evaluation of potential of these standards and protocols along with a detailed discussion on available hardware platforms, specific industrial energy harvesting techniques and their capabilities. The paper lists main service providers for IWSNs solutions and gives insight of future trends and research gaps in the field of IWSNs

A Highly Accurate Deep Learning Based Approach For Developing Wireless Sensor Network Middleware

Despite the popularity of wireless sensor networks (WSNs) in a wide range of applications, the security problems associated with WSNs have not been completely resolved. Since these applications deal with the transfer of sensitive data, protection from various attacks and intrusions is essential. From the current literature, we observed that existing security algorithms are not suitable for large-scale WSNs due to limitations in energy consumption, throughput, and overhead. Middleware is generally introduced as an intermediate layer between WSNs and the end user to address security challenges. However, literature suggests that most existing middleware only cater to intrusions and malicious attacks at the application level rather than during data transmission. This results in loss of nodes during data transmission, increased energy consumption, and increased overhead. In this research, we introduce an intelligent middleware based on an unsupervised learning technique called the Generative Adversarial Networks (GANs) algorithm. GANs contain two networks: a generator (G) network and a discriminator (D) network. The G network generates fake data that is identical to the data from the sensor nodes; it combines fake and real data to confuse the adversary and stop them from differentiating between the two. This technique completely eliminates the need for fake sensor nodes, which consume more power and reduce both throughput and the lifetime of the network. The D network contains multiple layers that have the ability to differentiate between real and fake data. The output intended for this algorithm shows an actual interpretation of the data that is securely communicated through the WSN. The framework is implemented in Python with experiments performed using Keras. The results illustrate that the suggested algorithm not only improves the accuracy of the data but also enhances its security by protecting it from attacks. Data transmission from the WSN to the end user then becomes much more secure and accurate compared to conventional techniques. Simulation results show that the proposed technique provides higher throughput and increases successful data rates while keeping the energy consumption low