Trajectory Privacy Preservation Based on a Fog Structure for Cloud Location Services

Wang, Tian; Zeng, Jiandian; Bhuiyan, Zakirul Alam; Tian, Hui; Cai, Yiqiao; Chen, Yonghong; Zhong, Bineng

doi:10.1109/access.2017.2698078

Cited by 95 publications

(34 citation statements)

References 34 publications

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“…In this context, Koo et al has presented a mixed secure paradigm that eliminates duplication by considering false fog saving and reserving scenarios [106]. For safeguarding of privacy, this work interjects a trusted third party (TPP) in the operation [107].…”

Section: Trust Middleware and Specimenmentioning

confidence: 99%

Fog Computing Architecture, Applications and Security Issues: A Survey

Neware¹

2019

Preprint

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The development of the Internet of Things (IoT) has triggered a virtual wave of interconnection and intercommunication among an enormous number of universal things. This has caused an exceptional surge of colossal heterogeneous information, known as an information explosion. Until now, cloud computing has filled in as a proficient method to process and store these data. Still, it came to light that by utilizing just cloud computing, pesky issues like, the expanding requests of actual-time or speed-sensitive applications and the restrictions on system transfer speed could not be solved. Consequently, another computing platform, called fog computing has been advanced as a supplement to the cloud arrangement. Fog computing spreads the cloud administrations and services to the edge of the system, and brings processing, communications and reserving and storage capacity closer to edge gadgets and end-clients and, in the process, aims at enhancing versatility, low latency, transfer speed and safety and protection. This paper takes an extensive and wide-ranging view of fog computing, covering several aspects. At the outset is outlined the many-layered structural design of fog computing and its attributes. After that, chief advances like communication and inter-exchange, computing, reserving and storage, asset administration, naming, safety and safeguarding of privacy are delineated while showing how this backup and facilitate the installations and various applications. Then, numerous applications like augmented reality (AR), healthcare, gaming and brain-machine interface, vehicular computing, smart scenarios etc. are highlighted to explain the fog computing application milieu. Following that, it is shown that how, despite fog computing being a features-rich platform, it is dogged by its susceptibility to several security, privacy and safety concerns, which stem from the nature of its widely distributed and open architecture. Finally, some suggestions are advanced to address some of the safety challenges discussed so as to propel the further growth of fog computing.

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Section: Trust Middleware and Specimenmentioning

confidence: 99%

Fog Computing Architecture, Applications and Security Issues: A Survey

Neware¹

2019

Preprint

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“…A, , ( ) = 1// to mark the data which is newly selected (23) W = W ∪ {d ( ) }// to select the new data (24) Renew Q A , C A (25) = + 1 (26) End if (27) End while (28) End for (29)…”

Section: Wireless Communications and Mobile Computing 11mentioning

confidence: 99%

“…In the end, vehicles flow in the city with greater mobility, which can bring great convenience to data collection. Vehicular communication networks, together with the cloud computing network [4,7,18,[24][25][26][27][28][29] as a key component of fog computing [7,24,25], provide the basis for the development of new network architectures.…”

Section: Introductionmentioning

confidence: 99%

Quality Utilization Aware Based Data Gathering for Vehicular Communication Networks

Ren

Liu

Zhao

et al. 2018

Wireless Communications and Mobile Computing

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The vehicular communication networks, which can employ mobile, intelligent sensing devices with participatory sensing to gather data, could be an efficient and economical way to build various applications based on big data. However, high quality data gathering for vehicular communication networks which is urgently needed faces a lot of challenges. So, in this paper, a fine-grained data collection framework is proposed to cope with these new challenges. Different from classical data gathering which concentrates on how to collect enough data to satisfy the requirements of applications, a Quality Utilization Aware Data Gathering (QUADG) scheme is proposed for vehicular communication networks to collect the most appropriate data and to best satisfy the multidimensional requirements (mainly including data gathering quantity, quality, and cost) of application. In QUADG scheme, the data sensing is fine-grained in which the data gathering time and data gathering area are divided into very fine granularity. A metric named “Quality Utilization” (QU) is to quantify the ratio of quality of the collected sensing data to the cost of the system. Three data collection algorithms are proposed. The first algorithm is to ensure that the application which has obtained the specified quantity of sensing data can minimize the cost and maximize data quality by maximizing QU. The second algorithm is to ensure that the application which has obtained two requests of application (the quantity and quality of data collection, or the quantity and cost of data collection) could maximize the QU. The third algorithm is to ensure that the application which aims to satisfy the requirements of quantity, quality, and cost of collected data simultaneously could maximize the QU. Finally, we compare our proposed scheme with the existing schemes via extensive simulations which well justify the effectiveness of our scheme.

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“…These sensing devices are deployed in a variety of applications and form the basis of Internet of Things (IoT) [34]. Combined with the current new cloud network [35], the formation of large-scale Social Networks by Fog computing [36] is rapidly changing all aspects of human production and life.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

Teng

Liu

et al. 2018

Wireless Communications and Mobile Computing

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In wireless sensor networks (WSNs), many applications require a high reliability for the sensing data forwarding to sink. Due to the lossy nature of wireless channels, achieving reliable communication through multihop forwarding can be very challenging. Broadcast technology is an effective way to improve the communication reliability so that the data can be received by multiple receiver nodes. As long as the data of any one of the receiver nodes is transmitted to the sink, the data can be transmitted successfully. In this paper, a cross-layer optimization protocol named Adaptive transmission Power control based Reliable data Forwarding (APRF) scheme by using broadcast technology is proposed to improve the reliability of network and reduce communication delay. The main contributions of this paper are as follows: (1) for general data aggregation sensor networks, through the theoretical analysis, the energy consumption characteristics of the network are obtained. (2) According to the case that the energy consumption of nearsink area is high and that in far-sink area is low, a cross-layer optimization method is adopted, which can effectively improve the data communication by increasing the transmission power of the remaining energy nodes. (3) Since the reliability of communication is improved by increasing the transmission power of the node, the number of retransmissions of the data packet is reduced, so that the delay of the packet reaching the sink node is reduced. The theoretical and experimental results show that, applying APRF scheme under initial transmission power of 0 dBm, although the lifetime dropped by 13.77%, delay could be reduced by 40.37%, network reliability could be reduced by 10.08%, and volume of data arriving at sink increased by 10.08% compared with retransmission-only mechanism.

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Trajectory Privacy Preservation Based on a Fog Structure for Cloud Location Services

Cited by 95 publications

References 34 publications

Fog Computing Architecture, Applications and Security Issues: A Survey

Fog Computing Architecture, Applications and Security Issues: A Survey

Quality Utilization Aware Based Data Gathering for Vehicular Communication Networks

Adaptive Transmission Power Control for Reliable Data Forwarding in Sensor Based Networks

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