Adaptive Application Configuration and Distribution in Mobile Cloudlet Middleware

Verbelen, Tim; Simoens, Pieter; Turck, Filip De; Dhoedt, Bart

doi:10.1007/978-3-642-36660-4_13

Cited by 8 publications

(11 citation statements)

References 17 publications

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“…We adopt the component-based cloudlet framework proposed in [22], [23] to create a collaborative cloudlet middleware. This cloudlet framework already provides the necessary functionality to offload software components from user devices to nearby computing infrastructure.…”

Section: Cloudlet Middlewarementioning

confidence: 99%

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Allocation Algorithms for Autonomous Management of Collaborative Cloudlets

Bohez

Verbelen

Simoens

et al. 2014

2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering

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Abstract-Mobile applications are evolving towards support for advanced interactivity and resource-demanding multimedia features. Mobile platforms are however struggling to cope with these new innovative application concepts, such as Augmented Reality, due to the inherent limitations on their available resources, such as CPU, memory and battery power. Offloading resource-intensive calculations to nearby infrastructure or devices, also known as cloudlets, has emerged as a viable alternative in offering interactive and resource-intensive applications to mobile users.This concept of resource sharing provides promising opportunities for collaborative scenarios in which not only data processing, but also the data itself are shared between multiple users. In this paper, we investigate the challenges posed by offloading collaborative mobile applications. We describe the problem of autonomous management of collaborative cloudlets and propose two heuristic algorithms, Simulated Annealing and Steepest Descent, in order to solve this optimization problem. We observe that these heuristics yield an effectiveness of more than 90% for execution times that are three orders of magnitude lower when compared to a guaranteed-optimal approach.

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Section: Cloudlet Middlewarementioning

confidence: 99%

“…This optimization problem can be formulated using a mathematical model of the collaborative cloudlet. We extend the cloudlet model presented in [23] by incorporating aspects of collaboration. There are three main aspects of the cloudlet model: the infrastructure, the components and their allocation, and the observed behaviour.…”

Section: A Cloudlet Modelmentioning

confidence: 99%

Allocation Algorithms for Autonomous Management of Collaborative Cloudlets

Bohez

Verbelen

Simoens

et al. 2014

2014 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering

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“…For example, available resources of proxies [34,56,57,64], the cost of user/the revenue of service provider [48,64], and the condition of communication links [54,56,65].…”

Section: Proxy Discoverymentioning

confidence: 99%

“…The authors proposed a decision algorithm in Verbelen et al [65] for the distribution of components of application among members of the cloudlet. The parameters taken into account for the decision making are the network condition, i.e.…”

Section: Partial Offload To Cloudletmentioning

confidence: 99%

“…Some of the work assumes that the mobile application can save information of all proxies e.g., Kemp et al [40], and some work assumes the presence of only one proxy to be used by all mobile applications e.g., [64,65,66]. These approaches are not applicable when the the number of mobile applications increases, or the number of proxies grows.…”

Section: Gap Analysismentioning

confidence: 99%

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A Proxy-Based Mobile Computing Infrastructure

Khalaj

Lutfiyya

Perry

2012

2012 Third FTRA International Conference on Mobile, Ubiquitous, and Intelligent Computing

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In recent years, there has been a huge growth in mobile applications. More mobile users are able to access Internet services via their mobile devices e.g., smartphones and tablets. Some of these applications are highly interactive and resource intensive. Mobile applications, with limited storage capacity, slow processors and limited battery life, could be connected to the remote servers in clouds for leveraging resources. For example, weather applications use a remote service that collects weather data and make this data available through a well-defined API. This represents a static partitioning of functionality between mobile devices and a remote server that is determined at run-time.Regardless of the network distance between the cloud infrastructure and the mobile device, the use of a remote service is well suited for mobile device applications with relatively little data to be transferred. However, long distances between a mobile device and remote services make this approach unsuitable for applications that require larger amounts of data to be transferred and/or have a high level of interactiveness with the user This includes mobile video communications (e.g., Skype, Face-Time, Google-Hangout), gaming applications that require sophisticated rendering and cloud media analysis that can be used to offer more personalized services. The latency incurred with this architecture makes it difficult to support real-time and interactive applications. A related problem is that the static partitioning strategy is not always suitable for all network conditions and inputs. For example, let us consider a speech recognition application. The performance depends on the size of the input and the type of connectivity to the backbone. Another challenge is that the communication medium between the mobile application and the remote service includes wireless links. Wireless links are more error prone and have less bandwidth than wired links. Often a mobile application may be disconnected.One approach to addressing these challenges is the use of a proxy. A proxy is computing power that is located at the network edge. This allows it to address problems with latency. It is possible for a proxy to have services that allow for offloading tasks from either the cloud or the mobile device and to deal with communication challenges between the mobile application and the mobile device.This work proposes a proxy-based system that acts as a middleware between the mobile application and the remote service. The proposed middleware consists of a set of proxies that provide services. The proposed middleware includes services for proxy discovery and selection, mechanisms for dealing with balancing loads on proxies and handoff. A prototype was developed to assess the effectiveness of the proposed proxy-based system.

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