scholarly journals MULTI-CLASS RESOURCE SHARING WITH PREEMPTIVE PRIORITIES

2017 ◽  
Vol 32 (3) ◽  
pp. 323-339
Author(s):  
Isi Mitrani
Keyword(s):  
Cost Function ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Resource Constraints ◽  
Optimal Number ◽  
Numerical Examples ◽  
Scheduling Policy ◽  
Preemptive Resume ◽  
Resource Requirements

Different virtual machines can share servers, subject to resource constraints. Incoming jobs whose resource requirements cannot be satisfied are queued and receive service according to a preemptive-resume scheduling policy. The problem is to evaluate a cost function, including holding and server costs, with a view to searching for the optimal number of servers. A model with two job types is analyzed exactly and the results are used to develop accurate approximations, which are then extended to more than two classes. Numerical examples and comparisons with simulations are presented.

scholarly journals MULTI-CLASS RESOURCE SHARING WITH BATCH ARRIVALS

2018 ◽  
Vol 33 (3) ◽  
pp. 348-366
Author(s):  
Paul Ezhilchelvan ◽  
Isi Mitrani
Keyword(s):  
Resource Sharing ◽  
Large Scale ◽  
Virtual Machines ◽  
Cloud Provider ◽  
Batch Arrivals ◽  
Large Scale Systems ◽  
Trade Offs ◽  
Resource Requirements ◽  
Partial Blocking ◽  
Fixed Point Iterations

A cloud provider hosts virtual machines (VMs) of different types, with different resource requirements. There are bounds on the total amounts of each kind of resource that are available. Requests arrive in batches of different sizes. Under the ‘complete blocking’ policy, a request is accepted only if all the VMs in its batch can be accommodated. The ‘partial blocking’ policy would accept a request if there is room for at least one of the VMs in the batch. Blocked requests are lost, with an associated loss of revenue. The trade-offs between costs and benefits are evaluated by means of appropriate models, for which novel solutions based on fixed-point iterations are proposed. The applicability of those solutions is extended, by means of simplifications, to very large-scale systems. Numerical examples and comparisons with simulations are presented.

scholarly journals A Multiserver User-space Unikernel for a Distributed Virtualization System

2019 ◽  
Author(s):  
Pablo Pessolani
Keyword(s):  
Service Oriented Architecture ◽  
Virtual Machines ◽  
Management Tools ◽  
Resource Requirements ◽  
Service Oriented ◽  
Small Footprint ◽  
Memory Network ◽  
User Space ◽  
Attack Surface ◽  
And Performance

Nowadays, most Cloud applications are developed using Service Oriented Architecture (SOA) or MicroService Architecture (MSA). The scalability and performance of them is achieved by executing multiple instances of its components in different nodes of a virtualization cluster. Initially, they were deployed in Virtual Machines (VMs) but, they required enough computational, memory, network and storage resources to hold an Operating System (OS), a set of utilities, libraries, and the application component. By deploying hundreds of these application components, the resource requirements increase a lot. To minimize them, usually small footprint OS are used. Later, as management tools were improved, the application components began to be deployed in Containers which require even less resources than VMs. Another way to reduce the resource requirements is integrating the application components in a Unikernel. This article proposes a Unikernel called MUK, based on a multiserver OS, to be used as a tool to integrate Cloud application components. MUK was built to run in user-space inside a Container of a Distributed Virtualization System. Both technologies facilitate the scattering of application components in a virtualization cluster keeping the isolation properties and minimal attack surface of a Unikernel.

scholarly journals Heuristic possibilistic clustering for detecting optimal number of elements in fuzzy clusters

2016 ◽  
Vol 41 (1) ◽  
pp. 45-76 ◽  
Author(s):  
Dmitri A. Viattchenin
Keyword(s):  
Optimal Number ◽  
Experimental Results ◽  
Numerical Examples ◽  
Relational Clustering ◽  
Possibilistic Clustering ◽  
Controls Cluster

AbstractThe paper deals with the problem of discovering fuzzy clusters with optimal number of elements in heuristic possibilistic clustering. The relational clustering procedure using a parameter that controls cluster sizes is considered and a technique for detecting the optimal number of elements in fuzzy clusters is proposed. The effectiveness of the proposed technique is illustrated through numerical examples. Experimental results are discussed and some preliminary conclusions are formulated.

scholarly journals Ensuring communication security in wireless sensor networks based on a multilevel protection architecture

2020 ◽  
Author(s):  
R. M. Boyarchuk ◽  
◽  
M. S. Pukha ◽  
A. P. Makovsʹkyy ◽  
K. D. Aystrakhanov ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Resource Constraints ◽  
Working Environment ◽  
Wireless Sensor ◽  
Communication Security ◽  
Network Systems ◽  
Resource Requirements ◽  
Efficient Resource ◽  
Individual Security

Wireless microsensor networks, which are used to monitor the physical environment, have become an important area of application for wireless technologies. The key attributes of these new types of network systems are strictly limited computing and energy resources, as well as a special working environment. This article examines aspects of the communication security of these networks. Resource constraints and the specific architecture of sensor networks require individual security mechanisms. Our approach is to classify the types of data that exist in sensor networks and identify potential threats to communication security according to this classification. We offer a communication security scheme, where for each data type we define the appropriate security mechanism. Using this multi-tiered security architecture, where each mechanism has different resource requirements, we provide efficient resource management, which is important for wireless sensor networks.

scholarly journals Project Portfolio Resource Risk Assessment considering Project Interdependency by the Fuzzy Bayesian Network

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-21
Author(s):  
Libiao Bai ◽  
Kaimin Zhang ◽  
Huijing Shi ◽  
Min An ◽  
Xiao Han
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Bayesian Network ◽  
Risk Reduction ◽  
Portfolio Management ◽  
Resource Sharing ◽  
Resource Constraints ◽  
Risk Level ◽  
Project Portfolio ◽  
Strategic Decisions

Resource risk caused by specific resource sharing or competition among projects due to resource constraints is a major issue in project portfolio management, which challenges the application of risk analysis methods effectively. This paper presents a methodology by using a fuzzy Bayesian network to assess the project portfolio resource risk, determine critical resource risk factors, and propose risk-reduction strategies. In this method, the project portfolio resource risk factors are first identified by taking project interdependency into consideration, and then the Bayesian network model is developed to analyze the risk level of the identified risk factors in which expert judgments and fuzzy set theory are integrated to determine the probabilities of all risk factors to deal with incomplete risk data and information. To reduce the subjectivity of expert judgments, the expert weights are determined by combining experts’ background and reliability degree of expert judgments. A numerical analysis is used to demonstrate the application of the proposed methodology. The results show that project portfolio resource risks can be analyzed effectively and efficiently. Furthermore, “poor communication and cooperation among projects,” “capital difficulty,” and “lack of sharing technology among projects” are considered the leading factors of the project portfolio resource risk. Risk-reduction strategic decisions based on the results of risk assessment can be made, which provide project managers with a useful method or tool to manage project risks.

A Virtual Machine Placement Algorithm with Energy-Efficiency in Cloud Computing

2017 ◽  
Vol 8 (2) ◽  
pp. 20-36
Author(s):  
Yu Cai
Keyword(s):  
Energy Efficiency ◽  
Energy Efficient ◽  
Virtual Machines ◽  
Live Migration ◽  
Vm Placement ◽  
Server Cluster ◽  
Simulated Environment ◽  
Resource Requirements ◽  
Placement Algorithm

Energy efficient virtual machines (VM) management and distribution on cloud platforms is an important research subject. Mapping VMs into PMs (Physical Machines) requires knowing the capacity of each PM and the resource requirements of the VMs. It should also take into accounts of VM operation overheads, the reliability of PMs, Quality of Service (QoS) in addition to energy efficiency. In this article, the authors propose an energy efficient statistical live VM placement scheme in a heterogeneous server cluster. Their scheme supports VM requests scheduling and live migration to minimize the number of active servers in order to save the overall energy in a virtualized server cluster. Specifically, the proposed VM placement scheme incorporates all VM operation overheads in the dynamic migration process. In addition, it considers other important factors in relation to energy consumption and is ready to be extended with more considerations on user demands. The authors conducted extensive evaluations based on HPC jobs in a simulated environment. The results prove the effectiveness of the proposed scheme.

Mobility-Aware Grid Computing

2011 ◽  
pp. 2626-2630
Author(s):  
Konstantinos Katsaros ◽  
George C. Polyzos
Keyword(s):  
Mobile Computing ◽  
Grid Computing ◽  
Resource Sharing ◽  
Large Scale ◽  
Resource Constraints ◽  
Mobile Users ◽  
Mobile Grid ◽  
Computing Environments ◽  
Hoc Networks ◽  
Simulation Signal

Grid computing has emerged as a paradigm for coordinated resource sharing and problem solving in dynamic, multiinstitutional virtual organizations (Foster, 2001). A grid computing system is essentially a large-scale distributed system designed to aggregate resources from multiple sites, giving to users the opportunity to take advantage of enormous computational, storage, or bandwidth resources that would otherwise be impossible to attain. Current applications of grid computing focus on computational-expensive processing of large volumes of scientific data, for example, for earthquake simulation, signal processing, cancer research, and pattern search in DNA sequences. At the same time, the recent advances in mobile and wireless communications have resulted in the availability of an enormous number of mobile computing devices such as laptop PCs and PDAs (personal digital assistants). Thus, it is natural to extend the idea of resource sharing to mobile and wireless computing environments. Resource-sharing collaboration between mobile users appears as a promising research direction toward the alleviation of the inherent resource constraints present in mobile computing environments. Either in the context of mobile ad hoc networks (MANETs) or in wireless networks based on fixed infrastructure (i.e., cellular networks, wireless local area networks (WLANs), small- or large-scale communities of mobile users can form mobile grid systems and collaborate in order to either achieve a common goal (otherwise impossible to achieve) or simply overcome their individual limitations. In the following, we highlight the fundamental issues toward the realization of a computational mobile grid system.

scholarly journals A Compromise Programming Model for Highway Maintenance Resources Allocation Problem

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Hui Xiong ◽  
Qixin Shi ◽  
Xianding Tao ◽  
Wuhong Wang
Keyword(s):  
Resource Sharing ◽  
Bridge Deck ◽  
Programming Model ◽  
Optimal Solution ◽  
Pavement Management ◽  
Compromise Programming ◽  
Resources Allocation ◽  
Final Solution ◽  
Highway Maintenance ◽  
Numerical Examples

This paper formulates a bilevel compromise programming model for allocating resources between pavement and bridge deck maintenances. The first level of the model aims to solve the resource allocation problems for pavement management and bridge deck maintenance, without considering resource sharing between them. At the second level, the model uses the results from the first step as an input and generates the final solution to the resource-sharing problem. To solve the model, the paper applies genetic algorithms to search for the optimal solution. We use a combination of two digits to represent different maintenance types. Results of numerical examples show that the conditions of both pavements and bridge decks are improved significantly by applying compromise programming, rather than conventional methods. Resources are also utilized more efficiently when the proposed method is applied.

scholarly journals Double auction and profit maximization mechanism for jobs with heterogeneous durations in cloud federations

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Runhao Lu ◽  
Yuning Liang ◽  
Qing Ling ◽  
Changle Li ◽  
Weigang Wu
Keyword(s):  
Job Scheduling ◽  
Virtual Machines ◽  
Profit Maximization ◽  
Resource Requirement ◽  
Resource Configuration ◽  
Ex Post ◽  
Resource Requirements ◽  
Trading Mechanism ◽  
Execution Times ◽  
The Individual

AbstractBy sharing resources with each other, different cloud providers in a cloud federation can exploit their diversity in resource configuration and operational cost so as to improve service performance. They should consider the strategy of resource pricing, job scheduling and server provisioning altogether to maximize their own interests. On the other hand, they need to efficiently trade the resources with a suitable mechanism, typically auction, so as to guarantee the participants’ profits. Nevertheless, in consideration of the heterogeneous execution times of jobs, both the pricing strategy and trading mechanism should be delicately designed, which is obviously a challenging task. In this paper, we firstly propose a truthful, individual-rational and ex-post budget-balanced auction mechanism for selecting pairs of buyer and seller winners to trade virtual machines for different durations. Then, to maximize the individual profits, we propose a dynamic resource bidding scheme and a job scheduling strategy based on our importance model of jobs with heterogeneous execution times and resource requirements. The simulation results show that, compared with existing ones, our design can better handle varieties of both execution time and resource requirement and make the participants obtain more individual profits.

scholarly journals Priority Based Mechanism for Resource Sharing in Cloud

2020 ◽  
Vol 9 (3) ◽  
pp. 311-316
Keyword(s):  
Cloud Computing ◽  
Load Balancing ◽  
Open Source ◽  
Resource Sharing ◽  
Virtual Machines ◽  
Service Providers ◽  
Priority Level ◽  
Lower Priority ◽  
Computing Technologies ◽  
Cloud Computing Service

Cloud computing technologies are getting matured day by day. Revolutions in underlying software, virtualization and hardware technologies related to storage, processing and computing technologies has helped cloud computing service providers to win trust of concerned stake holders. However, the exponentially increasing demand of cloud based resources has made task of resource management and utilization more and more challenging. A novel load balancing technique in cloud computing environment is presented in this paper. The virtual machines are implemented on an open source cloud computing platform on open source operating system. A virtual machines’ priorities based load balancing approach presented here indicates improvement in overall waiting time for load balancing. The mechanism prioritizes load balancing on same priority level virtual machines or lower priority level virtual machines.

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