CEER:Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

Underwater acoustic sensor networks(UWASNs)aim to find varied offshore ocean monitoring and exploration applications.In most of these applications,the network is composed of several sensor nodes deployed at different depths in the water.Sensor nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level;these nodes need multihop communication facilitated by a suitable routing scheme.In this research work,a Cluster-based Cooperative Energy Efficient Routing(CEER)mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH mechanisms.The optimal role of clustering and cooperation provides load balancing and improves the network profoundly.The simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol,i.e.,the average end-to-end delay of CEER was 17.39,Co-UWSN was 55.819 and LEACH was 70.08.In addition,the average total energy consumption of CEER was 9.273,Co-UWSN was 12.198,and LEACH was 45.33.The packet delivery ratio of CEER was 53.955,CO-UWSN was 42.047,and LEACH was 30.31.The stability period CEER was 130.9,CO-UWSN was 129.3,and LEACH was 119.1.The obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

基于动态定价的帧聚合策略(英文)

Frame aggregation is a wireless link optimization mechanism that aims to reduce transmission overheads by sending multiple frames as the payload of a single MAC frame. It is considered as one of the most efficient methods to improve the wireless channel utilization and the throughput of wireless networks.The static assignment of frame aggregation parameters can result in delay penalties due to variations in traffic type. We propose a frame aggregation scheme which is based on dynamic pricing and queue scheduling for a multitraffic scenario. The scheme adopts a dynamic differential pricing scheme for different types of traffic. Meanwhile, it polls buffer queues in accordance with the optimal aggregation weight factors to maximise the network revenue.Simulation results indicate that the proposed frame aggregation scheme can effectively improve the network revenue and the average throughput, while guaranteeing the delay requirements of all types of traffic.

Understanding Research Trends in Android Malware Research Using Information Modelling Techniques

Android has been dominating the smartphone market for more than a decade and has managed to capture 87.8%of the market share.Such popularity of Android has drawn the attention of cybercriminals and malware developers.The malicious applications can steal sensitive information like contacts,read personal messages,record calls,send messages to premium-rate numbers,cause financial loss,gain access to the gallery and can access the user’s geographic location.Numerous surveys on Android security have primarily focused on types of malware attack,their propagation,and techniques to mitigate them.To the best of our knowledge,Android malware literature has never been explored using information modelling techniques.Further,promulgation of contemporary research trends in Android malware research has never been done from semantic point of view.This paper intends to identify intellectual core from Android malware literature using Latent Semantic Analysis(LSA).An extensive corpus of 843 articles on Android malware and security,published during 2009–2019,were processed using LSA.Subsequently,the truncated singular Value Decomposition(SVD)technique was used for dimensionality reduction.Later,machine learning methods were deployed to effectively segregate prominent topic solutions with minimal bias.Apropos to observed term and document loading matrix values,this five core research areas and twenty research trends were identified.Further,potential future research directions have been detailed to offer a quick reference for information scientists.The study concludes to the fact that Android security is crucial for pervasive Android devices.Static analysis is the most widely investigated core area within Android security research and is expected to remain in trend in near future.Research trends indicate the need for a faster yet effective model to detect Android applications causing obfuscation,financial attacks and stealing user information.

EA-RDSP: Energy Aware Rapidly Deployable Wireless Ad hoc System for Post Disaster Management

In post disaster scenarios such as war zones floods and earthquakes,the cellular communication infrastructure can be lost or severely damaged.In such emergency situations,remaining in contact with other rescue response teams in order to provide inputs for both headquarters and disaster survivors becomes very necessary.Therefore,in this research work,a design,implementation and evaluation of energy aware rapidly deployable system named EA-RDSP is proposed.The proposed research work assists the early rescue workers and victims to transmit their location information towards the remotely located servers.In EA-RDSP,two algorithms are proposed i.e.,Hop count Assignment(HCA)algorithm and Maximum Neighbor Selection(MNS)algorithm.The EA-RDSP contains three types of nodes;the client node sends information about casualty in the disaster area to the server,the relay nodes transmit this information from client node to server nodes via multi-hop transmission,the server node receives messages sent by client node to alert rescue teams.The EAM-RDSP contains three types of nodes;the client node sends information about casualty in the disaster area to the server,the relay nodes transmit this information from client node to server nodes via multi-hop transmission,the server node receives messages sent by client node to alert rescue teams.The proposed EA-RDSP scheme is simulated using NS2 simulator and its performance is compared with existing scheme in terms of end-to-end delay,message delivery ratio,network overhead and energy consumption.