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Zeng Zhiwen
School of computer science and engineering, central south university, Changsha 410083 China

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Journal article
Published: 31 May 2021 in Computer Networks
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Convergence of Augmented Reality (AR) and Next Generation Internet-of-Things (NG-IoT) can create new opportunities in many emerging areas, where the real-time data can be visualized on the devices. Integrated NG-IoT network, AR can improve efficiency in many fields such as mobile computing, smart city, intelligent transportation and telemedicine. However, limited by capability of mobile device, the reliability and latency requirements of AR applications is difficult to meet by local processing. To solve this problem, we study a binary offloading scheme for AR edge computing. Based on the proposed model, the parts of AR computing can offload to edge network servers, which is extend the computing capability of mobile AR devices. Moreover, a deep reinforcement learning offloading model is considered to acquire B5G network resource allocation and optimally AR offloading decisions. First, this offloading model does not need to solve combinatorial optimization, which is greatly reduced the computational complexity. Then the wireless channel gains and binary offloading states is modeled as a Markov decision process, and solved by deep reinforcement learning. Numerical results show that our scheme can achieve better performance compared with existing optimization methods.

ACS Style

Miaojiang Chen; Wei Liu; Tian Wang; Anfeng Liu; Zhiwen Zeng. Edge intelligence computing for mobile augmented reality with deep reinforcement learning approach. Computer Networks 2021, 195, 108186 .

AMA Style

Miaojiang Chen, Wei Liu, Tian Wang, Anfeng Liu, Zhiwen Zeng. Edge intelligence computing for mobile augmented reality with deep reinforcement learning approach. Computer Networks. 2021; 195 ():108186.

Chicago/Turabian Style

Miaojiang Chen; Wei Liu; Tian Wang; Anfeng Liu; Zhiwen Zeng. 2021. "Edge intelligence computing for mobile augmented reality with deep reinforcement learning approach." Computer Networks 195, no. : 108186.

Research article
Published: 01 May 2019 in IET Communications
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Wireless sensor network (WSN) can reduce human labour and monitoring difficulties in forest fire prevention and environment monitoring due to its low power consumption, small size, self-organising, flexible setting, and unattended operation. However, the limited WSN hardware resources and power capacity, the practical application requirements such as real-time monitoring and timely warning of emergencies, pose higher challenges to WSN on its lifespan, reliability, and real-time performance. This paper proposes a QoS adaptive and energy aware cross-layer opportunistic routing protocol (QE-COR). The protocol sets an adaptive QoS function Qi comprehensively considering multiple metrics, through which the best forwarding node can be selected, and the QoS of transmission can adaptively adjust according to the data's needs. The protocol can also select a standby node to start retransmission when forwarding errors occur. A RTS-QACK and an ASS-DATA-SACK response mechanisms are designed to improve the transmission efficiency and avoid message conflicts. The sleep mechanism of MAC layer related with node's working state enables dynamical switching between active and sleep modes, which improves the energy utilisation and the flexibility of the network. Compared with similar opportunistic routing protocols, QE-COR can improve energy utilisation and extend network lifetime, while ensuring transmission reliability and end-to-end delay performance.

ACS Style

Qi Huamei; Jiang Tao; Jiang Su; Zeng Zhiwen; Xiong Wangping. QoS adaptive and energy aware cross‐layer opportunistic routing protocol in wireless sensor networks. IET Communications 2019, 13, 1034 -1042.

AMA Style

Qi Huamei, Jiang Tao, Jiang Su, Zeng Zhiwen, Xiong Wangping. QoS adaptive and energy aware cross‐layer opportunistic routing protocol in wireless sensor networks. IET Communications. 2019; 13 (8):1034-1042.

Chicago/Turabian Style

Qi Huamei; Jiang Tao; Jiang Su; Zeng Zhiwen; Xiong Wangping. 2019. "QoS adaptive and energy aware cross‐layer opportunistic routing protocol in wireless sensor networks." IET Communications 13, no. 8: 1034-1042.

Journal article
Published: 20 November 2018 in Sensors
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By using Software Defined Network (SDN) technology, senor nodes can get updated program code which can provide new features, so it has received extensive attention. How to effectively spread code to each node fast is a challenge issue in wireless sensor networks (WSNs). In this paper, an Adding Active Slot joint Larger Broadcast Radius (AAS-LBR) scheme is proposed for fast code dissemination. The AAS-LBR scheme combines the energy of data collection and code dissemination, making full use of the remaining energy in the far-sink area to increase the active slot and the broadcast radius to speed up the code dissemination. The main contributions of the proposed AAS-LBR scheme are the following: (1) Make full use of the remaining energy of the far sink area to expand the broadcast radius, so that the node broadcasts a longer distance. The wide range of broadcasts makes the number of nodes receiving code more, which speeds up the spread of code dissemination. (2) AAS-LBR uses two improved methods to further reduce the number of broadcasts and speed up the code dissemination: (a) When constructing the broadcast backbone whose nodes dominate all nodes in network and are responsible for broadcasting code, the active slot is added to the next hop node in a pipeline style on the diffusion path, which enables the code dissemination process to continue without pause. Thus, the code can quickly spread to the entire broadcast backbone. (b) For the nodes in the non-broadcast backbone whose nodes are dominated by the broadcast backbone and only for receiving code, an active slot is added coincident with its broadcast backbone' active slot, which can reduce the time required for code dissemination and reduce the number of broadcasts. A lot of performance analysis and simulation results show that compared to previous schemed, the AAS-LBR scheme can balance energy consumption, the transmission delay can be reduced 43.09⁻78.69%, the number of broadcasts can be reduced 44.51⁻86.18% and the energy efficiency is improved by about 24.5%.

ACS Style

Wei Yang; Wei Liu; Zhiwen Zeng; Anfeng Liu; Guosheng Huang; Neal N. Xiong; Zhiping Cai. Adding Active Slot Joint Larger Broadcast Radius for Fast Code Dissemination in WSNs. Sensors 2018, 18, 4055 .

AMA Style

Wei Yang, Wei Liu, Zhiwen Zeng, Anfeng Liu, Guosheng Huang, Neal N. Xiong, Zhiping Cai. Adding Active Slot Joint Larger Broadcast Radius for Fast Code Dissemination in WSNs. Sensors. 2018; 18 (11):4055.

Chicago/Turabian Style

Wei Yang; Wei Liu; Zhiwen Zeng; Anfeng Liu; Guosheng Huang; Neal N. Xiong; Zhiping Cai. 2018. "Adding Active Slot Joint Larger Broadcast Radius for Fast Code Dissemination in WSNs." Sensors 18, no. 11: 4055.

Journal article
Published: 29 May 2018 in Sensors
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Hundreds of thousands of ubiquitous sensing (US) devices have provided an enormous number of data for Information-Centric Networking (ICN), which is an emerging network architecture that has the potential to solve a great variety of issues faced by the traditional network. A Caching Joint Shortcut Routing (CJSR) scheme is proposed in this paper to improve the Quality of service (QoS) for ICN. The CJSR scheme mainly has two innovations which are different from other in-network caching schemes: (1) Two routing shortcuts are set up to reduce the length of routing paths. Because of some inconvenient transmission processes, the routing paths of previous schemes are prolonged, and users can only request data from Data Centers (DCs) until the data have been uploaded from Data Producers (DPs) to DCs. Hence, the first kind of shortcut is built from DPs to users directly. This shortcut could release the burden of whole network and reduce delay. Moreover, in the second shortcut routing method, a Content Router (CR) which could yield shorter length of uploading routing path from DPs to DCs is chosen, and then data packets are uploaded through this chosen CR. In this method, the uploading path shares some segments with the pre-caching path, thus the overall length of routing paths is reduced. (2) The second innovation of the CJSR scheme is that a cooperative pre-caching mechanism is proposed so that QoS could have a further increase. Besides being used in downloading routing, the pre-caching mechanism can also be used when data packets are uploaded towards DCs. Combining uploading and downloading pre-caching, the cooperative pre-caching mechanism exhibits high performance in different situations. Furthermore, to address the scarcity of storage size, an algorithm that could make use of storage from idle CRs is proposed. After comparing the proposed scheme with five existing schemes via simulations, experiments results reveal that the CJSR scheme could reduce the total number of processed interest packets by 54.8%, enhance the cache hits of each CR and reduce the number of total hop counts by 51.6% and cut down the length of routing path for users to obtain their interested data by 28.6–85.7% compared with the traditional NDN scheme. Moreover, the length of uploading routing path could be decreased by 8.3–33.3%.

ACS Style

Baixiang Huang; Anfeng Liu; Chengyuan Zhang; Naixue Xiong; Zhiwen Zeng; Zhiping Cai. Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking. Sensors 2018, 18, 1750 .

AMA Style

Baixiang Huang, Anfeng Liu, Chengyuan Zhang, Naixue Xiong, Zhiwen Zeng, Zhiping Cai. Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking. Sensors. 2018; 18 (6):1750.

Chicago/Turabian Style

Baixiang Huang; Anfeng Liu; Chengyuan Zhang; Naixue Xiong; Zhiwen Zeng; Zhiping Cai. 2018. "Caching Joint Shortcut Routing to Improve Quality of Service for Information-Centric Networking." Sensors 18, no. 6: 1750.

Journal article
Published: 16 April 2018 in Sensors
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The quality of service (QoS) regarding delay, lifetime and reliability is the key to the application of wireless sensor networks (WSNs). Data aggregation is a method to effectively reduce the data transmission volume and improve the lifetime of a network. In the previous study, a common strategy required that data wait in the queue. When the length of the queue is greater than or equal to the predetermined aggregation threshold ( N t ) or the waiting time is equal to the aggregation timer ( T t ), data are forwarded at the expense of an increase in the delay. The primary contributions of the proposed Adaptive Aggregation Routing (AAR) scheme are the following: (a) the senders select the forwarding node dynamically according to the length of the data queue, which effectively reduces the delay. In the AAR scheme, the senders send data to the nodes with a long data queue. The advantages are that first, the nodes with a long data queue need a small amount of data to perform aggregation; therefore, the transmitted data can be fully utilized to make these nodes aggregate. Second, this scheme balances the aggregating and data sending load; thus, the lifetime increases. (b) An improved AAR scheme is proposed to improve the QoS. The aggregation deadline ( T t ) and the aggregation threshold ( N t ) are dynamically changed in the network. In WSNs, nodes far from the sink have residual energy because these nodes transmit less data than the other nodes. In the improved AAR scheme, the nodes far from the sink have a small value of T t and N t to reduce delay, and the nodes near the sink are set to a large value of T t and N t to reduce energy consumption. Thus, the end to end delay is reduced, a longer lifetime is achieved, and the residual energy is fully used. Simulation results demonstrate that compared with the previous scheme, the performance of the AAR scheme is improved. This scheme reduces the delay by 14.91%, improves the lifetime by 30.91%, and increases energy efficiency by 76.40%.

ACS Style

Xujing Li; Anfeng Liu; Mande Xie; Neal N. Xiong; Zhiwen Zeng; Zhiping Cai. Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks. Sensors 2018, 18, 1216 .

AMA Style

Xujing Li, Anfeng Liu, Mande Xie, Neal N. Xiong, Zhiwen Zeng, Zhiping Cai. Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks. Sensors. 2018; 18 (4):1216.

Chicago/Turabian Style

Xujing Li; Anfeng Liu; Mande Xie; Neal N. Xiong; Zhiwen Zeng; Zhiping Cai. 2018. "Adaptive Aggregation Routing to Reduce Delay for Multi-Layer Wireless Sensor Networks." Sensors 18, no. 4: 1216.

Journal article
Published: 01 March 2018 in Sensors
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The Internet of things (IoT) is composed of billions of sensing devices that are subject to threats stemming from increasing reliance on communications technologies. A Trust-Based Secure Routing (TBSR) scheme using the traceback approach is proposed to improve the security of data routing and maximize the use of available energy in Energy-Harvesting Wireless Sensor Networks (EHWSNs). The main contributions of a TBSR are (a) the source nodes send data and notification to sinks through disjoint paths, separately; in such a mechanism, the data and notification can be verified independently to ensure their security. (b) Furthermore, the data and notification adopt a dynamic probability of marking and logging approach during the routing. Therefore, when attacked, the network will adopt the traceback approach to locate and clear malicious nodes to ensure security. The probability of marking is determined based on the level of battery remaining; when nodes harvest more energy, the probability of marking is higher, which can improve network security. Because if the probability of marking is higher, the number of marked nodes on the data packet routing path will be more, and the sink will be more likely to trace back the data packet routing path and find malicious nodes according to this notification. When data packets are routed again, they tend to bypass these malicious nodes, which make the success rate of routing higher and lead to improved network security. When the battery level is low, the probability of marking will be decreased, which is able to save energy. For logging, when the battery level is high, the network adopts a larger probability of marking and smaller probability of logging to transmit notification to the sink, which can reserve enough storage space to meet the storage demand for the period of the battery on low level; when the battery level is low, increasing the probability of logging can reduce energy consumption. After the level of battery remaining is high enough, nodes then send the notification which was logged before to the sink. Compared with past solutions, our results indicate that the performance of the TBSR scheme has been improved comprehensively; it can effectively increase the quantity of notification received by the sink by 20%, increase energy efficiency by 11%, reduce the maximum storage capacity needed by nodes by 33.3% and improve the success rate of routing by approximately 16.30%.

ACS Style

Jiawei Tang; Anfeng Liu; Jian Zhang; Neal N. Xiong; Zhiwen Zeng; Tian Wang. A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks. Sensors 2018, 18, 751 .

AMA Style

Jiawei Tang, Anfeng Liu, Jian Zhang, Neal N. Xiong, Zhiwen Zeng, Tian Wang. A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks. Sensors. 2018; 18 (3):751.

Chicago/Turabian Style

Jiawei Tang; Anfeng Liu; Jian Zhang; Neal N. Xiong; Zhiwen Zeng; Tian Wang. 2018. "A Trust-Based Secure Routing Scheme Using the Traceback Approach for Energy-Harvesting Wireless Sensor Networks." Sensors 18, no. 3: 751.