Utility maximisation for resource allocation of migrating enterprise applications into the cloud

Li, Shiyong; Sun, Wei

doi:10.1080/17517575.2020.1730445

Cited by 26 publications

(13 citation statements)

References 56 publications

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“…Besides resource pricing schemes, reputation-based mechanisms are also used to promote cooperation between selfish peers and achieve reasonable resource allocation for peers. For example, Satsiou and Tassiulas ( 2010 ) assumed each peer could earn its reputation analogous to its contributions and presented a reputation-based resource allocation scheme. Later, Gupta et al.…”

Section: Related Workmentioning

confidence: 99%

“…Since the utility functions of elastic services are usually concave, then the resource allocation problem for elastic services is a convex optimization problem, which can be solved through the first order Lagrangian method. Besides resource pricing mechanisms, reputation-based methods are also used to encourage cooperation amongst selfish peers so as to promote each peer to provide resource for others and achieve efficient resource allocation, e.g., Satsiou and Tassiulas ( 2010 ), Gupta et al. ( 2016 ) and Goswami et al.…”

Section: Introductionmentioning

confidence: 99%

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Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation

Sun

Huan

2021

Oper Res Int J

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Peer-to-peer (P2P) networks support a wide variety of network services including elastic services such as file-sharing and downloading and inelastic services such as real-time multiparty conferencing. Each peer who acquires a service will receive a certain level of satisfaction if the service is provided with a certain amount of resource. The utility function is used to describe the satisfaction of a peer when acquiring a service. In this paper we consider optimal resource allocation for elastic and inelastic services and formulate a utility maximization model which is an intractable and difficult non-convex optimization problem. In order to resolve it, we apply the successive approximation method and approximate the non-convex problem to a serial of equivalent convex optimization problems. Then we develop a gradientbased resource allocation scheme to achieve the optimal solutions of the approximations. After a serial of approximations, the proposed scheme can finally converge to an optimal solution of the primal utility maximization model for resource allocation which satisfies the Karush-Kuhn-Tucker conditions.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation

Sun

Huan

2021

Oper Res Int J

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“…In the above Equation (2),

refers to the willingness to pay (WTP) of customer

for processing the tasks with low requirement on latency and high requirement on processing capacity [ 46 , 47 ]. In the above Equation (3).…”

Section: Resource Allocation Model Of Edge Computing Without Usingmentioning

confidence: 99%

Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach

Liu

Sun

2020

Sensors

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Recently, more and more smart homes have become one of important parts of home infrastructure. However, most of the smart home applications are not interconnected and remain isolated. They use the cloud center as the control platform, which increases the risk of link congestion and data security. Thus, in the future, smart homes based on edge computing without using cloud center become an important research area. In this paper, we assume that all applications in a smart home environment are composed of edge nodes and users. In order to maximize the utility of users, we assume that all users and edge nodes are placed in a market and formulate a pricing resource allocation model with utility maximization. We apply the Lagrangian method to analyze the model, so an edge node (provider in the market) allocates its resources to a user (customer in the market) based on the prices of resources and the utility related to the preference of users. To obtain the optimal resource allocation, we propose a pricing-based resource allocation algorithm by using low-pass filtering scheme and conform that the proposed algorithm can achieve an optimum within reasonable convergence times through some numerical examples.

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“…Under the various attacks, the effect of the experiment is shown in Table 8. It Standardization of service type data: service type (assignment) http (1) smtp 2Fingers 3Eco_i 4ftp_data (5) ftp (6) Domain_u (7) Hostnames (8) Imap4 (9) mtp (10) Netstat (11) Private (12) Systat (13) Telnet (14) ecr_i (15) Time (16) uucp (17) Login (18) urp_i (19) Pop_3 20Auth (21) Other (21) URP_I (22) Others 23Standardization of property data: property type (assignment) REJ 1S1 2…”

Section: Simulation Backgroundmentioning

confidence: 99%

“…Nowadays, the Internet is dramatically growing with the proliferation of a wide variety of network-connected devices everywhere. As increasing numbers of applications are continuously migrated from these devices to the cloud [1], current cloud infrastructure has become too overwhelmed to provide guaranteed services. For instance, the massive multisource data and resource-consuming computing tasks generated from these devices go far beyond the ability of cloud computing technologies [2].…”

Section: Introductionmentioning

confidence: 99%

An Edge IDS Based on Biological Immune Principles for Dynamic Threat Detection

Jia

Wang

2020

Wireless Communications and Mobile Computing

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Edge computing solves such questions as the massive multisource data and resource consuming computing tasks in edge devices. Some new security problems especially the data security and privacy issues have been introduced into the edge computing scenario. Through analyzing the biological immune principles, a novel idea for the problem of intrusion detection in edge computing is provided. Specifically, an edge intrusion detection system (Edge IDS) with a distributed structure, which has the characteristics of an imprecise model, self-learning, and strong interactivity, is constructed in a systematic way inspired by the biological immune principles. Moreover, a newly proposed gene immune detection algorithm (GIDA) is designed. In order that Edge IDS can deal with the dynamic data problem efficiently, the key functional components such as the remaining gene, niching strategy, and extracting vaccine are embedded into the GIDA algorithm. Furthermore, extensive simulation experiments are conducted, and the results show that the proposed Edge IDS can be adapted to the domain of edge computing with comparative performance advantages.

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Utility maximisation for resource allocation of migrating enterprise applications into the cloud

Cited by 26 publications

References 56 publications

Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation

Optimal resource allocation for multiclass services in peer-to-peer networks via successive approximation

Resource Allocation for Edge Computing without Using Cloud Center in Smart Home Environment: A Pricing Approach

An Edge IDS Based on Biological Immune Principles for Dynamic Threat Detection

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