Zhenjiang Zhang

High energy‐efficient and privacy‐preserving secure data aggregation for wireless sensor networks

SUMMARY An efficient data process technology is needed for wireless sensor networks composed of many sensors with constrained communication, computational, and memory resources. Data aggregation is presented as an efficient and significant method to reduce transmitted data and prolong lifetime for wireless sensor networks. Meanwhile, many applications require preserving privacy for secure data aggregation. In this paper, we propose a high energy-efficient and privacy-preserving scheme for secure data aggregation. Because of the importance of communication overhead and accuracy, our scheme achieves less communication overhead and higher data accuracy besides providing for privacy preservation. For extensive simulations, we evaluate and conclude the performance of our high energy-efficient and privacy-preserving scheme. The conclusion shows that the high energy-efficient and privacy-preserving scheme provides better privacy preservation and is more efficient than existing schemes. Copyright

Improved Reliable Trust-Based and Energy-Efficient Data Aggregation for Wireless Sensor Networks

In wireless sensor networks, secure data aggregation is very important for reducing the quantity of data transmitted and prolonging the lifetime of wireless sensor networks. When wireless sensor networks are deployed in untrusted and hostile environments, their nodes are often compromised, which reduces the security and reliability of the transmitted data. Compromised nodes can inject erroneous data, selectively forward data to an adversary, impersonate legal nodes to join routing paths, and disrupt data transmission during the data-aggregation operation. Previous researchers have relied on reputation system to find compromised nodes and prevent attacks during the data-aggregation operation. In this paper, we propose an improved reliable, trust-based, and energy-efficient data-aggregation protocol for wireless sensor networks. We call the protocol the iRTEDA protocol, and it combines the reputation system, residual energy, link availability, and a recovery mechanism to improve secure data aggregation and ensure that the network is secure, reliable, and energy-efficient. Simulations have shown that the iRTEDA protocol exceeds the performances of other protocols from the perspectives of the accuracy of the data, the reliability of the routing path, the consumption of energy, and the lifetime of secure data aggregation.

Cooperative Fog Computing for Dealing with Big Data in the Internet of Vehicles: Architecture and Hierarchical Resource Management

As vehicle applications, mobile devices and the Internet of Things are growing fast, and developing an efficient architecture to deal with the big data in the Internet of Vehicles (IoV) has been an important concern for the future smart city. To overcome the inherent defect of centralized data processing in cloud computing, fog computing has been proposed by offloading computation tasks to local fog servers (LFSs). By considering factors like latency, mobility, localization, and scalability, this article proposes a regional cooperative fog-computing-based intelligent vehicular network (CFC-IoV) architecture for dealing with big IoV data in the smart city. Possible services for IoV applications are discussed, including mobility control, multi-source data acquisition, distributed computation and storage, and multi-path data transmission. A hierarchical model with intra-fog and inter-fog resource management is presented, and energy efficiency and packet dropping rates of LFSs in CFC-IoV are optimized.

Study on the energy efficiency based on improved LEACH in wireless sensor networks

Energy efficiency and data reliability have always been the key problem in WSN. In this paper, firstly, a selection of cluster head algorithm is designed which is able to detect the energy change of nodes, rapidly ascertain new cluster head, and avoid excessive energy consumption between cluster head and cluster nodes. Secondly, differentiated service is introduced in our algorithm which makes achieve higher data reliability. Finally, evaluating our algorithm reliability and energy consumption, the simulation results show that it obtains higher data reliability, and simultaneously achieves lower energy consumption.

OPINION DYNAMICS IN POPULATIONS WITH IMPLICIT COMMUNITY STRUCTURE

Web encounter facilitate contacts between people from different communities outside space and time. Implicit Community Structure is exhibited because of highly connected links within community and sparse encounters between communities. Considering the imperceptible influence of encounter on opinions, Sznajd updating rules are used to mimic peoples behaviors after encountering a stranger in another community. We introduce a model for opinion evolution, in which the interconnectivity between different communities is represented as encounter frequency, and leadership is introduced to control the strength of communitys opinion guide. In this scenario, the effects of Implicit Community Structure of contact network on opinion evolution, for asymmetric and random initial distribution but with heterogeneous opinion guide, are investigated respectively. It is shown that large encounter frequency favors consensus of the whole populations and successful opinion spreading, which is qualitatively agree with the results observed in Majority model defined on substrates with predefined community structure.

An Energy-Efficient Motion Strategy for Mobile Sensors in Mixed Wireless Sensor Networks

The mixed wireless sensor networks that are composed of a mixture of mobile and static sensors are the tradeoff between cost and coverage. To provide the required high coverage, the mobile sensors have to move from dense areas to sparse areas. However, where to move and how to move are important issues for mobile sensors. This paper presents a centralized algorithm to assist the movement of mobile sensors. In this algorithm, the management node of the WSN collected the geographical information of all of the static and mobile sensors. Then, the management node executed the algorithm to get the best matches between mobile sensors and coverage holes. Simulation results show the effectiveness of our algorithm, in terms of saving energy and the load balance.

GABs: a game-based secure and energy efficient data aggregation for wireless sensor networks

This paper endeavors to investigate the security and energy issues in wireless sensor networks from prior art such as game theory and various embodiments of methods like public-key cryptography. Due to the needs of interacting with the physical world, thanks to a plethora of innovative applications, the state of the art in wireless sensor networks (WSNs) is focusing on multiple purposes such as monitoring, tracking, and security while relying upon some assumptions about distributed data, whereas these assumptions may not hold in a real scenario. The content herein models homogeneous WSN environment of highly linked nodes, in a theoretical game with synchronized actions, where, in order to transmit their readings securely across the network in some level of hierarchy, using the technique of data aggregation, sensor nodes with communication and computational resources constraint should establish trusted and direct links between their neighbors for the privacy and integrity of their data against faulty nodes, while ensuring energy saving. The study considers the ZigBee known as IEEE 802.15.4 standard for its high trustworthiness and low power consumption in wireless sensor network and compares different topology models.

A Novel Method Defends against the Path-Based DoS for Wireless Sensor Network

WSNs are significantly different from the traditional network architecture due to its wireless communication, energy limitation, and computation constraint and environment of the application. Because of these differences, security becomes a critical issue. The path-based denial of service (PDoS) attacks harm the network maintenance and cause serious damage in the resource constrained WSNs. In a PDoS attack, an adversary can overwhelm sensor node and cluster head node to flood packets along the routing path so that intermediate node must keep active mode and exhaust the energy. In this paper, we creatively propose a novel method, which is operated at the base station to detect the malicious behavior. The proposed method is combined with triple exponential smoothing and Markov chain, so that it makes the detection results more accurate. Meanwhile, we first use the concept of black hole to defend the PDoS attack in WSNs. Simulation results are provided to evaluate the performance and illustrate the contribution of this mechanism.

DYNAMICS WITH CO-EVOLUTION OF INDIVIDUAL INCLINATION AND OPINION

Based on the voter model, we present a new opinion formation model which takes into account the evolution of both opinions and individual inclinations. A memory-based inclination is developed gradually during the process of social interaction; however, if the individual inclination gets strong enough, it will react to opinion dynamics. We assume that an individual inclination increases with the number of times the individual has held its most frequent opinion in the past interactions. As a result of inclination choices the transition rate following neighbors decreases, thus slowing down the microscopic dynamics. Analytical and simulation results indicate the system under the action of opinion inclinations evolves to a more polarized state for average opinion. The appearance of extremists holding the minority opinion is observed in the final state, where one opinion predominates. It is also found that the stable opinion and relaxation time depend on network topology and memory length. Moreover, this model is not only valid to the voter model, but can also be applied to other spin systems.

Green alarm systems driven by emergencies in industrial wireless sensor networks

An alarm system is a fundamental application of IWSNs. Most of the existing literature focuses on reliability and quality of service of alarm systems. In addition, timeliness is another big concern for alarm systems considering the serious consequences of various emergencies. However, with the explosion of energy consumption, energy efficiency is becoming more and more important for IWSNs. Improving energy efficiency effectively without reducing other performance of alarm systems is a severe challenge. In this article, we design a novel green framework of alarm systems for the industrial field based on the IWSN. The proposed framework is composed of two parts, the IWSN and the security sector, which are connected through wireless links. The main responsibility of the IWSN is to monitor and track emergency and deliver the collected data to the security sector; the main responsibility of the security sector is to store and analyze the received data stream, and send requests to the IWSN. In IWSN, sleeping schedules and routing algorithms are designed carefully to improve the energy efficiency, reliability, and timeliness of alarm systems. Tracking emergencies and reducing redundant nodes are also necessary. The security sector stores and analyzes a data stream, and then evaluates an emergency situation. At last, the estimated emergency situation is used to trigger some corresponding actions to tackle the emergency.