Enhanced source location privacy and prolonged network lifetime are imperative for WSNs-the skin of IoT. To address these issues, a novel technique named source location privacy with enhanced privacy ...and network lifetime (SLP-E) is proposed. It employs a reverse random walk followed by a walk on annular rings, to create divergent routing paths in the network, and finally, min-hop routing together with the walk on dynamic rings to send the packets to the base station (BS). The existing random walk-based SLP approaches have either focused on enhancing only privacy at the cost of network lifetime (NLT) or have aimed at improving the amount of privacy without degrading the network lifetime performance. Unlike these schemes, the objectives of the proposed work are to simultaneously improve the safety period and network lifetime along with achieving uniform privacy. This combination of improvements has not been considered so far in a single SLP random walk-based scheme. Additionally, this study investigates for the first time the impact of the sensors' radio range on both privacy strength and network lifetime metrics in the context of SLP within WSNs. The performance measurements conducted using the proposed analytical models and the simulation results indicate an improvement in the safety period and network lifespan. The safety period in SLP-E increased by 26.5%, 97%, 123%, and 15.7% when compared with SLP-R, SRR, PRLPRW, and PSSLP techniques, respectively. Similarly, the network lifetime of SLP-E increased by 17.36%, 0.2%, 83.41%, and 13.42% when compared with SLP-R, SRR, PRLPRW, and PSSLP techniques, respectively. No matter where a source node is located within a network, the SLP-E provides uniform and improved privacy and network lifetime. Further, the simulation results demonstrate that the sensors' radio range has an impact on the safety period, capture ratio, and the network lifetime.
Privacy of critical locations (or events) is essential when monitored by wireless sensor networks. To mitigate such issues, in this article, a new privacy protection technique named ...position-independent and section-based source location privacy (PSSLP) is developed. A biased random walk and greedy walk using a three- or four-phase routing strategy is employed here, where the number of phases depends on the network segment in which the source is situated. The biased random walk is intended to send packets away from the source of information and make routing paths appear dynamic to the eavesdropper, whereas, the greedy routing ensures that the packets converge at the base station. The objective of the solution is to achieve a uniform amount of privacy irrespective of the position of the asset in the network without compromising the network lifetime. Performance evaluation is done using developed analytical models and simulation results reveal that PSSLP achieves 8247.06- and 33.0- folds improvement in terms safety period and network lifetime, respectively, compared to no SLP protection technique (i.e., shortest path routing technique).
Monitoring System to Strive against Fall Armyworm in Crops Case Study: Maize in Rwanda Hanyurwimfura, Damien; Nizeyimana, Eric; Ndikumana, Faustine ...
2018 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)
Conference Proceeding
The food security has received much attention due the hunger that usually affects some countries in Africa. Pests are very dangerous to crops and reduce the harvest of affected crop and can cause ...risk if no technical methods are applied to strive against them. Fall armyworm (FAW) is one the pest that has attacked the priority stable crop of Rwanda (maize) since last year 2017. This reduced the expected harvest from this crop. The presence of this pest costs the government to use drones and other special forces to strive for it, but pest will remain a problem if there is no regular, automatic way to detect the pest and strive for it at the early days of attacking the crop. This paper introduces a design of a prototype of an automated system that will be able to detect the presence of a fall armyworm in the field. The system will use the new technology of Internet of Things (IoT) where sensors are used to identify the pest location. Once the presence of the pest is detected in the farm, the system will be able to give the information of the affected crop and notify the farmer through his/her mobile phone who will immediately react accordingly. Through the authorization from the farmer, the system will be able to pump pesticides to kill both larvae and eggs of fall armyworm on the affected crop. This automated system will save the farmer's time, as it will monitor the crops while the farmer is occupied with other activities. Lastly the system will help to increase the production of maize in Rwanda since the crop will be safe from the pest.
Remote monitoring in wireless sensor networks (WSNs) requires enhanced privacy and long-term monitoring of objects or events without escalating delay. To address this problem, a strategic random walk ...routing for protecting source location privacy (SRWSLP) in wireless sensor networks (WSNs) is proposed in this article. The proposed technique routes the packets from the source node to the base station (BS) using three phases of routing, namely: i) adaptive backward random walk (A-BRW), ii) adaptive equal depth routing (A-EDR), and iii) forward random walk (FRW). In order to give an impression to a backtracking attacker that the routing pathways are dynamic, the A-BRW and A-EDR phases are designed to carefully route the packets away from the source node in the first two phases of routing. In the third phase, the packets are sent to the base station (BS) using the forward random walk. The objective of the solution is to achieve improved privacy and network lifetime without affecting delay. Simulation results have demonstrated that the proposed technique performs better than the existing random walk class of SLP techniques.
