Operational Cost of Running Real-Time Mobile Cloud Applications

2016 ◽  
pp. 1111-1137
Author(s):  
Ovunc Kocabas ◽  
Regina Gyampoh-Vidogah ◽  
Tolga Soyata
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Service Level ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Cost Models ◽  
Operational Cost ◽  
Resource Requirements ◽  
The Cost ◽  
Cloud Applications

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.

Operational Cost of Running Real-Time Mobile Cloud Applications

2015 ◽  
pp. 294-321 ◽  
Author(s):  
Ovunc Kocabas ◽  
Regina Gyampoh-Vidogah ◽  
Tolga Soyata
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Service Level ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Cost Models ◽  
Operational Cost ◽  
Resource Requirements ◽  
The Cost ◽  
Cloud Applications

This chapter describes the concepts and cost models used for determining the cost of providing cloud services to mobile applications using different pricing models. Two recently implemented mobile-cloud applications are studied in terms of both the cost of providing such services by the cloud operator, and the cost of operating them by the cloud user. Computing resource requirements of both applications are identified and worksheets are presented to demonstrate how businesses can estimate the operational cost of implementing such real-time mobile cloud applications at a large scale, as well as how much cloud operators can profit from providing resources for these applications. In addition, the nature of available service level agreements (SLA) and the importance of quality of service (QoS) specifications within these SLAs are emphasized and explained for mobile cloud application deployment.

scholarly journals A LAYERED FRAMEWORK FOR CONNECTING CLIENT OBJECTIVES AND RESOURCE CAPABILITIES

2006 ◽  
Vol 15 (03) ◽  
pp. 391-413 ◽  
Author(s):  
ASIT DAN ◽  
KAVITHA RANGANATHAN ◽  
CATALIN L. DUMITRESCU ◽  
MATEI RIPEANU
Keyword(s):  
Service Provider ◽  
Large Scale ◽  
Service Management ◽  
Service Level ◽  
Performance Criteria ◽  
Management Scenarios ◽  
Levels Of Abstraction ◽  
Resource Requirements ◽  
And Performance ◽  
High Level

In large-scale, distributed systems such as Grids, an agreement between a client and a service provider specifies service level objectives both as expressions of client requirements and as provider assurances. From an application perspective, these objectives should be expressed in a high-level, service or application-specific manner rather than requiring clients to detail the necessary resources. Resource providers on the other hand, expect low-level, resource-specific performance criteria that are uniform across applications and can be easily interpreted and provisioned. This paper presents a framework for service management that addresses this gap between high-level specification of client performance objectives and existing resource management infrastructures. The paper identifies three levels of abstraction for resource requirements a service provider needs to manage, namely: detailed specification of raw resources, virtualization of heterogeneous resources as abstract resources, and performance objectives at an application level. The paper also identifies three key functions for managing service-level agreements, namely: translation of resource requirements across abstraction layers, arbitration in allocating resources to client requests, and aggregation and allocation of resources from multiple lower-level resource managers. One or more of these key functions may be present at each abstraction layer of a service-level manager. Thus, layering and the composition of these functions across abstraction layers enables modeling of a wide array of management scenarios. The framework we present uses service metadata and/or service performance models to map client requirements to resource capabilities, uses business value associated with objectives to arbitrate between competing requests, and allocates resources based on previously negotiated agreements. We instantiate this framework for three different scenarios and explain how the architectural principles we introduce are used in the real-word.

scholarly journals Blockchain-enabled real-time SLA monitoring for cloud-hosted services

2021 ◽  
Author(s):  
Kashif Mehboob Khan ◽  
Junaid Arshad ◽  
Waheed Iqbal ◽  
Sidrah Abdullah ◽  
Hassan Zaib
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Service Providers ◽  
Response Times ◽  
Cloud Service ◽  
Service Level ◽  
Cloud Services ◽  
Blockchain Technology ◽  
Manual Processing ◽  
And Performance

AbstractCloud computing is an important technology for businesses and individual users to obtain computing resources over the Internet on-demand and flexibly. Although cloud computing has been adopted across diverse applications, the owners of time-and-performance critical applications require cloud service providers’ guarantees about their services, such as availability and response times. Service Level Agreements (SLAs) are a mechanism to communicate and enforce such guarantees typically represented as service level objectives (SLOs), and financial penalties are imposed on SLO violations. Due to delays and inaccuracies caused by manual processing, an automatic method to periodically verify SLA terms in a transparent and trustworthy manner is fundamental to effective SLA monitoring, leading to the acceptance and credibility of such service to the customers of cloud services. This paper presents a blockchain-based distributed infrastructure that leverages fundamental blockchain properties to achieve immutable and trustworthy SLA monitoring within cloud services. The paper carries out an in-depth empirical investigation for the scalability of the proposed system in order to address the challenge of transparently enforcing real-time monitoring of cloud-hosted services leveraging blockchain technology. This will enable all the stakeholders to enforce accurate execution of SLA without any imprecisions and delays by maintaining an immutable ledger publicly across blockchain network. The experimentation takes into consideration several attributes of blockchain which are critical in achieving optimum performance. The paper also investigates key characteristics of these factors and their impact to the behaviour of the system for further scaling it up under various cases for increased service utilization.

scholarly journals The Italian TREETALKER NETWORK (ITT-Net): continuous large scale monitoring of tree functional traits and vulnerabilities to climate change

2020 ◽  
Author(s):  
Simona Castaldi ◽  
Serena Antonucci ◽  
Shahla Asgharina ◽  
Giovanna Battipaglia ◽  
Luca Belelli Marchesini ◽  
...  
Keyword(s):  
Climate Change ◽  
Real Time ◽  
High Frequency ◽  
Large Scale ◽  
Operation Mode ◽  
Cloud Services ◽  
Long Term Monitoring ◽  
The Impact ◽  
Term Monitoring

<p>The  <strong>Italian TREETALKER NETWORK (ITT-Net) </strong>aims to respond to one of the grand societal challenges: the impact of climate changes on forests ecosystem services and forest dieback. The comprehension of the link between these phenomena requires to complement the most classical approaches with a new monitoring paradigm based on large scale, single tree, high frequency and long-term monitoring tree physiology, which, at present, is limited by the still elevated costs of multi-sensor devices, their energy demand and maintenance not always suitable for monitoring in remote areas. The ITT-Net network will be a unique and unprecedented worldwide example of real time, large scale, high frequency and long-term monitoring of tree physiological parameters. By spring 2020, as part of a national funded project (PRIN) the network will have set 37 sites from the north-east Alps to Sicily where a new low cost, multisensor technology “the TreeTalker®” equipped to measure tree radial growth, sap flow, transmitted light spectral components related to foliage dieback and physiology and plant stability (developed by Nature 4.0), will monitor over 600 individual trees. A radio LoRa protocol for data transmission and access to cloud services will allow to transmit in real time high frequency data on the WEB cloud with a unique IoT identifier to a common database where big data analysis will be performed to explore the causal dependency of climate events and environmental disturbances with tree functionality and resilience.</p><p>With this new network, we aim to create a new knowledge, introducing a massive data observation and analysis, about the frequency, intensity and dynamical patterns of climate anomalies perturbation on plant physiological response dynamics in order to: 1) characterize the space of “normal or safe tree operation mode” during average climatic conditions; 2) identify the non-linear tree responses beyond the safe operation mode, induced by extreme events, and the tipping points; 3) test the possibility to use a high frequency continuous monitoring system to identify early warning signals of tree stress which might allow to follow tree dynamics under climate change in real time at a resolution and accuracy that cannot always be provided through forest inventories or remote sensing technologies.</p><p>To have an overview of the ITT Network you can visit www.globaltreetalker.org</p><p> </p>

scholarly journals An Empirical Study on Peer-to-Peer Sharing of Resources in Mobile Cloud Environment

2018 ◽  
Vol 8 (3) ◽  
pp. 1933
Author(s):  
R. K. Nadesh ◽  
M. Aramudhan
Keyword(s):  
Real World ◽  
Large Scale ◽  
Cloud Model ◽  
Cloud Service ◽  
Mobile User ◽  
Peer To Peer ◽  
Cloud Services ◽  
Mobile Cloud ◽  
Real World Application ◽  
File Formats

The increase usage of mobile users with internet and interoperability among the cloud services intensifies the role of distributed environemtnt in today’s real world application. Modern technologies are important for building rich, scalable and interoperable applications. To meet the requirements of client,the cloud service provider should offer adequate infrastructure especially under heavy multi-client load.To provide solution for large scale requirements and to statisfy the mobile client from the critical situation like lacking with bandwidth,connectivity issues,service completion ratio, we present adhoc virtual cloud model  for different scenarios that include single and multiple client configurations with various file sizes of various file formats for retrieving files in the mobile cloud environement.We evaluate the strategies with the socket and RMI implemented using java and identify the best model for real world applications. Performance evaluation is done with the results obtained and recommends that when sockets and RMI can be appropriately used in peer-to-peer environment when the mobile user cannot connect directly to the cloud services.

scholarly journals MG-DVD: A Real-time Framework for Malware Variant Detection Based on Dynamic Heterogeneous Graph Learning

2021 ◽  
Author(s):  
Chen Liu ◽  
Bo Li ◽  
Jun Zhao ◽  
Ming Su ◽  
Xu-Dong Liu
Keyword(s):  
Real Time ◽  
Real World ◽  
Large Scale ◽  
State Of The Art ◽  
Evolutionary Patterns ◽  
Graph Learning ◽  
Fine Grained ◽  
Variant Detection ◽  
Effectiveness And Efficiency ◽  
The Cost

Detecting the newly emerging malware variants in real time is crucial for mitigating cyber risks and proactively blocking intrusions. In this paper, we propose MG-DVD, a novel detection framework based on dynamic heterogeneous graph learning, to detect malware variants in real time. Particularly, MG-DVD first models the fine-grained execution event streams of malware variants into dynamic heterogeneous graphs and investigates real-world meta-graphs between malware objects, which can effectively characterize more discriminative malicious evolutionary patterns between malware and their variants. Then, MG-DVD presents two dynamic walk-based heterogeneous graph learning methods to learn more comprehensive representations of malware variants, which significantly reduces the cost of the entire graph retraining. As a result, MG-DVD is equipped with the ability to detect malware variants in real time, and it presents better interpretability by introducing meaningful meta-graphs. Comprehensive experiments on large-scale samples prove that our proposed MG-DVD outperforms state-of-the-art methods in detecting malware variants in terms of effectiveness and efficiency.

MDE Approach for the Establishment of a Service Level Agreements Monitoring by Trusted Third Party in the Cloud Computing

2015 ◽  
Vol 7 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Adil Maarouf ◽  
Mahmoud El Hamlaoui ◽  
Abderrahim Marzouk ◽  
Abdelkrim Haqiq
Keyword(s):  
Cloud Computing ◽  
Real Time ◽  
Critical Issue ◽  
Service Level ◽  
Cloud Services ◽  
Third Party ◽  
Cloud Provider ◽  
Service Level Agreements ◽  
Trusted Third Party ◽  
Model Driven

Establishing and monitoring SLA violations in real-time has become a critical issue for Cloud Computing. In this paper the authors investigate this issue and propose a model to express the SLA contract requirements using Model Driven Engineering (MDE), as a mean for establishing service level agreements between a cloud provider and cloud customer in the context of a particular service provision. The participation of a Trusted Third Party (TTP) may be necessary in order to resolve conflicts between prospective signatories, likewise to monitor SLA violations in real-time in the goal to ensure online monitoring cloud services and provide better than best-effort behavior for clouds. The main focus of this work is firstly to use MDE technology for the creation of the SLA contract and then to integrate TTP that should be able to apply an advanced penalty model that guarantees the performance and the reliability of the Cloud.

scholarly journals Modified PSO Algorithm for Real-Time Energy Management in Grid-Connected Microgrids

2018 ◽  
Author(s):  
Md Alamgir Hossain ◽  
Hemanshu Roy Pota ◽  
Stefano Squartini ◽  
Ahmed Fathi Abdou
Keyword(s):  
Cost Function ◽  
Real Time ◽  
Energy Management ◽  
Storage System ◽  
Pso Algorithm ◽  
Operational Cost ◽  
Electricity Pricing ◽  
Optimal Operating ◽  
The Cost ◽  
Operating Points

Real-time energy management of a converter-based microgrid is difficult to determine optimal operating points of a storage system in order to save costs and minimise energy waste. This complexity arises due to time-varying electricity prices, stochastic energy sources and power demand. Many countries have imposed real-time electricity pricing to efficiently control demand side management. This paper presents a particle swarm optimisation (PSO) for the application of real-time energy management to find optimal battery controls of a community microgrid. The modification of the PSO consists in altering the cost function to better model the battery charging/discharging operations. As optimal control is performed by formulating an cost function, it is suitably analysed and then a dynamic penalty function to obtain the best cost function is proposed. Several case studies with different scenarios are conducted to determine the effectiveness of the proposed cost function. The proposed cost function can reduce operational cost by 12% as compared to the original cost function over a time horizon of 96 hours. Simulation results reveal the suitability of applying the regularised PSO algorithm with the proposed cost function, which can be adjusted according to the need of the community, for the real-time energy management.

scholarly journals Real-time, selective, and low-cost detection of trace level SARS-CoV-2 spike-protein for cold-chain food quarantine

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Jian Zhang ◽  
Xin Fang ◽  
Yu Mao ◽  
Haochen Qi ◽  
Jayne Wu ◽  
...  
Keyword(s):  
Real Time ◽  
Large Scale ◽  
Limit Of Detection ◽  
Low Cost ◽  
Spike Protein ◽  
Cold Chain ◽  
Trace Level ◽  
Interdigitated Microelectrode ◽  
The Cost ◽  
Virus Survival

AbstractDue to the friendly temperature for virus survival, SARS-CoV-2 is frequently found in cold-chain foods, posing a serious threat to public health. Utilizing an interdigitated microelectrode chip modified with an antibody probe and integrating dielectrophoresis enrichment with interfacial capacitance sensing, a strategy is presented for the detection of trace level spike-protein from SARS-CoV-2. It achieves a limit of detection as low as 2.29 × 10−6 ng/mL in 20 s, with a wide linear range of 10−5–10−1 ng/mL and a selectivity of 234:1. The cost for a single test can be controlled to ~1 dollar. This strategy provides a competitive solution for real-time, sensitive, selective, and large-scale application in cold-chain food quarantine.

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