It is generally accepted that the edge computing paradigm is regarded as capable of satisfying the resource requirements for the emerging mobile applications such as the Internet of Things (IoT) ones. Undoubtedly, the data collected by underlying sensor networks are the foundation of both the IoT systems and IoT applications. However, due to the weakness and vulnerability to attacks of underlying sensor networks, the data collected are usually untrustworthy, which may cause disastrous consequences. In this article, a new model is proposed to collect trustworthy data on the basis of edge computing in the IoT. In this model, the sensor nodes are evaluated from multiple dimensions to obtain accurately quantified trust values. Besides, by mapping the trust value of a node onto a force for the mobile data collector, the best mobility path is generated with high trust. Moreover, a mobile edge data collector is used to visit both the sensors with quantified trust values and collect trustworthy data. The extensive experiment validates that the IoT systems based on trustworthy data collection model gain a significant improvement in their performance, in terms of both system security and energy conservation. © 2014 IEEE.

Arun Kumar S

Department of Information Security

School of Computer Science and Engineering

Vellore Campus

Md Zakirul Alam Bhuiyan

Lei Qiu

Tian Wang

Anfeng Liu

Ying Ma

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

&nbsp;

&nbsp;

VIT University

IEEE Internet of Things Journal

In wireless sensor networks (WSNs), sensor devices must be equipped with the capabilities of sensing, computation and communication. These devices work continuously through non-rechargeable batteries under harsh conditions, the batter span of nodes determines the whole network lifetime. Network clustering adopts an energy neutral approach to extend the network life. The clustering methods can be divided into even and uneven clustering. If even clustering is adopted, it will cause the cluster head nodes (CHs) in vicinity of the base station to relay more data and cause energy hole phenomenon. Therefore, we adopt a non-uniform clustering method to alleviate the problem of energy hole. Furthermore, to further balance and remit resource overhead of the entire network, we combined the PEGASIS algorithm and the Hamilton loop algorithm, through a mixture of single-hop and multiple hops mechanisms, inserting a mobile agent node (MA) and designing an optimal empower Hamilton loop is obtained by the local optimization algorithm. MA is responsible for receiving and fusing packet from the CHs on the path. Network performance results show that the proposed routing algorithm can effectively prolong network lifetime, equalize resource expenditure and decrease the propagation delay. © 2019, The Author(s).

Fulltext

Human-centric Computing and Information Sciences

An empower hamilton loop based data collection algorithm with mobile agent for WSNs

The smart grid solves the growing load demand of electrical customers through two-way real-time communication of electricity supply and demand sides and home energy management system (HEMS). However, these technical features also bring network security risks to the real-time price signal of the smart grid. The real-time price attack (RTPA) can maliciously raise the real-time price in smart meter, resulting in an increase in electrical customers load demand, causing the extensive damage to the power transmission lines due to overload. In this paper, we based on the behavioral relationship between load demand of electrical customers and real-time price of electricity suppliers (ES), defined the game relationship between RTPA, ES, and electrical customers, established a price elasticity of electricity demand (PEED) model, and proposed a defensive strategy of real-time price attack based on multiperson zero-determinant strategy (MPZDS). The experimental results show that the combination of MPZDS to some extent cut the expected load demand of electrical customers and protect the safety of power transmission lines.

Security and Communication Networks

Research on Defensive Strategy of Real-Time Price Attack Based on Multiperson Zero-Determinant

Future Generation Computer Systems

A novel trust mechanism based on Fog Computing in Sensor–Cloud System

Complexity and Algorithms for Superposed Data Uploading Problem in Networks With Smart Devices

IEEE Transactions on Industrial Informatics

Energy-Efficient and Trustworthy Data Collection Protocol Based on Mobile Fog Computing in Internet of Things

Edge-Computing-Based Trustworthy Data Collection Model in the Internet of Things

Journal	Data powered by TypesetIEEE Internet of Things Journal
Publisher	Data powered by TypesetInstitute of Electrical and Electronics Engineers (IEEE)
ISSN	23274662
Open Access	0