scispace - formally typeset
Search or ask a question
Author

Dhanya .K

Bio: Dhanya .K is an academic researcher from University of Cambridge. The author has contributed to research in topics: Mobile computing & Provisioning. The author has an hindex of 1, co-authored 1 publications receiving 99 citations.

Papers
More filters
Journal Article
TL;DR: Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing.
Abstract: Mobile devices such as smart phones and tablets have become an essential part of our lives, because of their powerful capabilities Along with the explosive growth of the mobile applications and up-raising cloud computing concept, mobile cloud computing appears to be a new potential technology for mobile services Mobile cloud computing maps cloud computing ideas and overcomes obstacles that deal with performance such as battery life, CPU, storage, bandwidth, environment that means heterogeneity, scalability, availability and security discussed in mobile computing To solve these problems by accessing cloud computing platforms To access these platforms is not always guaranteed to be available and is too expensive to access themTo overcome this issue by creating a virtual cloud computing platform using mobile phones

99 citations


Cited by
More filters
Journal ArticleDOI
TL;DR: Compared to the local execution and the remote execution, the collaborative task execution can significantly save the energy consumption on the mobile device, prolonging its battery life and applying the LARAC algorithm to solving the optimization problem approximately, which has lower complexity than the enumeration algorithm.
Abstract: This paper investigates collaborative task execution between a mobile device and a cloud clone for mobile applications under a stochastic wireless channel. A mobile application is modeled as a sequence of tasks that can be executed on the mobile device or on the cloud clone. We aim to minimize the energy consumption on the mobile device while meeting a time deadline, by strategically offloading tasks to the cloud. We formulate the collaborative task execution as a constrained shortest path problem. We derive a one-climb policy by characterizing the optimal solution and then propose an enumeration algorithm for the collaborative task execution in polynomial time. Further, we apply the LARAC algorithm to solving the optimization problem approximately, which has lower complexity than the enumeration algorithm. Simulation results show that the approximate solution of the LARAC algorithm is close to the optimal solution of the enumeration algorithm. In addition, we consider a probabilistic time deadline, which is transformed to hard deadline by Markov inequality. Moreover, compared to the local execution and the remote execution, the collaborative task execution can significantly save the energy consumption on the mobile device, prolonging its battery life.

248 citations

Journal ArticleDOI
01 Dec 2017
TL;DR: A comprehensive review of the prevalent Edge Cloud Computing frameworks and approaches is presented with a detailed comparison of its classifications through various QoS metrics (pertinent to network performance and overheads associated with deployment/migration) and provides a comprehensive overview on sate-of-the-art and future research directions for multi-access mobile edge computing.
Abstract: Latency minimization is a pivotal aspect in provision of real time services while adhering to Quality of Experience (QoE) parameters for assuring spectral efficiency. Edge Cloud Computing, being a potential research dimension in the realm of 5G networks, targets to enhance the network efficiency by harnessing effectiveness of both cloud computing and mobile devices in user's proximity. Keeping in view the far ranging impact of Edge Cloud Computing in future mobile generations, a comprehensive review of the prevalent Edge Cloud Computing frameworks and approaches is presented with a detailed comparison of its classifications through various QoS metrics (pertinent to network performance and overheads associated with deployment/migration). Considering the knowledge accumulated, procedures analysed and theories discussed, the paper provides a comprehensive overview on sate-of-the-art and future research directions for multi-access mobile edge computing.

120 citations

Journal ArticleDOI
TL;DR: An efficient task reassignment strategy based on the critical path of the directed acyclic graph modeling the applications is proposed to refine the output schedules of the Cost-Makespan aware Scheduling algorithm to satisfy the user-defined deadline constraints or quality of service of the system.
Abstract: The rapid development of Internet of Things applications, along with the limitations of cloud computing due mainly to the far distance between Internet of Thing devices and cloud-based platform, ha...

114 citations

Journal ArticleDOI
TL;DR: A comprehensive review of the research field from a multi-dimensional view based on application goal, realizing approach, offloading direction, etc, and presents a complete introductory guide to the researches relevant to opportunistic offloading.
Abstract: This paper surveys the literature of opportunistic offloading. Opportunistic offloading refers to offloading traffic originally transmitted through the cellular network to opportunistic network, or offloading computing tasks originally executed locally to nearby devices with idle computing resources through opportunistic network. This research direction is recently emerged, and the relevant research covers the period from 2009 to date, with an explosive trend over the last four years. We provide a comprehensive review of the research field from a multi-dimensional view based on application goal, realizing approach, offloading direction, etc. In addition, we pinpoint the major classifications of opportunistic offloading, so as to form a hierarchical or graded classification of the existing works. Specifically, we divide opportunistic offloading into two main categories based on application goal: traffic offloading or computation offloading. Each category is further divided into two smaller categories: with and without offloading node selection, which bridges between subscriber node and the cellular network, or plays the role of computing task executor for other nodes. We elaborate, compare, and analyze the literatures in each classification from the perspectives of required information, objective, etc. We present a complete introductory guide to the researches relevant to opportunistic offloading. After summarizing the development of the research direction and offloading strategies of the current state-of-the-art, we further point out the important future research problems and directions.

108 citations

Journal ArticleDOI
01 Nov 2016
TL;DR: This study surveys the state-of-the-art research efforts carried out in the MAC domain, and advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles.
Abstract: The unabated flurry of research activities to augment various mobile devices in terms of compute-intensive task execution by leveraging heterogeneous resources of available devices in the local vicinity has created a new research domain called mobile ad hoc cloud MAC or mobile cloud. It is a new type of mobile cloud computing MCC. MAC is deemed to be a candidate blueprint for future compute-intensive applications with the aim of delivering high functionalities and rich impressive experience to mobile users. However, MAC is yet in its infancy, and a comprehensive survey of the domain is still lacking. In this paper, we survey the state-of-the-art research efforts carried out in the MAC domain. We analyze several problems inhibiting the adoption of MAC and review corresponding solutions by devising a taxonomy. Moreover, MAC roots are analyzed and taxonomized as architectural components, applications, objectives, characteristics, execution model, scheduling type, formation technologies, and node types. The similarities and differences among existing proposed solutions by highlighting the advantages and disadvantages are also investigated. We also compare the literature based on objectives. Furthermore, our study advocates that the problems stem from the intrinsic characteristics of MAC by identifying several new principles. Lastly, several open research challenges such as incentives, heterogeneity-ware task allocation, mobility, minimal data exchange, and security and privacy are presented as future research directions. Copyright © 2016 John Wiley & Sons, Ltd.

101 citations