Modeling and Analyzing the Reliability and Cost of Service Composition in the IoT: A Probabilistic Approach

Li, Lixing; Jin, Zhi; Li, Ge; Zheng, Lihua; Wei, Qiang

doi:10.1109/icws.2012.25

Cited by 65 publications

(29 citation statements)

References 14 publications

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“…In the context of IoT deployments, formal modelling approaches have been recently proposed to achieve connectivity and coverage optimisation [20], [21], improved resource exploitation of Wireless Sensors Networks [22], and to estimate reliability and cost of service compositions [23]. Our modelling effort aims at complementing that work, by describing the interactions among software components and IoT devices at a higher level of abstraction to achieve segmentation of applications through the Fog-that, to the best of our knowledge, was not addressed by previous work.…”

Section: Related Workmentioning

confidence: 99%

QoS-Aware Deployment of IoT Applications Through the Fog

Brogi

Forti

2017

IEEE Internet Things J.

401

262

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Abstract-Fog computing aims at extending the Cloud by bringing computational power, storage and communication capabilities to the edge of the network, in support of the IoT. Segmentation, distribution and adaptive deployment of functionalities over the continuum from Things to Cloud are challenging tasks, due to the intrinsic heterogeneity, hierarchical structure and very large scale infrastructure they will have to exploit.In this paper we propose a simple, yet general, model to support the QoS-aware deployment of multi-component IoT applications over Fog infrastructures. The model describes operational systemic qualities of the available infrastructure (latency and bandwidth), interactions among software components and Things, and business policies. Algorithms to determine eligible deployment plans for an application over a Fog infrastructure are presented. A Java tool, FogTorch, based on the proposed model has been prototyped.

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Section: Related Workmentioning

confidence: 99%

QoS-Aware Deployment of IoT Applications Through the Fog

Brogi

Forti

2017

IEEE Internet Things J.

401

262

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“…The authors of [107] propose a reliability scheme at the transmission level to minimize packet losses. Other authors [108] exploit probabilistic model methods to evaluate the reliability and cost-related properties of the service composition in IoT systems. The survey [109] reviews applications of the Markov decision process (MDP) framework, a powerful decision-making tool to develop adaptive algorithms and protocols for WSNs, like data exchange and topology formation, resource and power optimization, area coverage, event tracking solutions, and security and intrusion detection methods.…”

Section: Operational Requirementsmentioning

confidence: 99%

A Review on Internet of Things for Defense and Public Safety

Fraga‐Lamas

Fernández‐Caramés

Suárez-Albela

et al. 2016

Sensors

194

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The Internet of Things (IoT) is undeniably transforming the way that organizations communicate and organize everyday businesses and industrial procedures. Its adoption has proven well suited for sectors that manage a large number of assets and coordinate complex and distributed processes. This survey analyzes the great potential for applying IoT technologies (i.e., data-driven applications or embedded automation and intelligent adaptive systems) to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where Defense and Public Safety (PS) could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. This article reviews the main tactical requirements and the architecture, examining gaps and shortcomings in existing IoT systems across the military field and mission-critical scenarios. The review characterizes the open challenges for a broad deployment and presents a research roadmap for enabling an affordable IoT for defense and PS.

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“…From a perspective of Web service interactive environment, the paper [17] used timed automata and TCTL (time computation tree logic) to express the time-related behaviors and properties of the IoT service respectively, and used the model checking tool UPPAAL to verify the timeliness and correctness of the IoT service. The paper [18] used Markov decision process and PCTL (probabilistic computation tree logic) to describe the reliability and the resource consumption-related behaviors and properties of the IoT service, and used the probabilistic model checking tool (PRISM) to verify them. Then the strategy of the IoT service composition which is suitable for the certain reliability and resource consumption could be selected.…”

Section: Related Workmentioning

confidence: 99%

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

Zhang

Chou

2016

Sensors

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The service of sensor device in Emerging Sensor Networks (ESNs) is the extension of traditional Web services. Through the sensor network, the service of sensor device can communicate directly with the entity in the geographic environment, and even impact the geographic entity directly. The interaction between the sensor device in ESNs and geographic environment is very complex, and the interaction modeling is a challenging problem. This paper proposed a novel Petri Nets-based modeling method for the interaction between the sensor device and the geographic environment. The feature of the sensor device service in ESNs is more easily affected by the geographic environment than the traditional Web service. Therefore, the response time, the fault-tolerant ability and the resource consumption become important factors in the performance of the whole sensor application system. Thus, this paper classified IoT services as Sensing services and Controlling services according to the interaction between IoT service and geographic entity, and classified GIS services as data services and processing services. Then, this paper designed and analyzed service algebra and Colored Petri Nets model to modeling the geo-feature, IoT service, GIS service and the interaction process between the sensor and the geographic enviroment. At last, the modeling process is discussed by examples.

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Modeling and Analyzing the Reliability and Cost of Service Composition in the IoT: A Probabilistic Approach

Cited by 65 publications

References 14 publications

QoS-Aware Deployment of IoT Applications Through the Fog

QoS-Aware Deployment of IoT Applications Through the Fog

A Review on Internet of Things for Defense and Public Safety

A Novel Petri Nets-Based Modeling Method for the Interaction between the Sensor and the Geographic Environment in Emerging Sensor Networks

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