The localization problem plays a vital role in the services provided by wireless sensor network (WSN). Under non-ideal conditions, the transmit power is different and the clock is not synchronized. The measured received signal strength (RSS) and time of arrival (TOA) are subjected to deviation. In this paper, a novel algorithm was proposed to alleviate these impact on localization accuracy and reduce computing consumption of localization. The algorithm called generalized trust region subproblem with improved weights (GTRS-IW) transforms the original non-convex problem into a framework of generalized trust region subproblem and solves it through a bisection process. Additionally, a critical distance was introduced to improve the weights. The proposed GTRS-IW achieves precise localization accuracy with lower computation time and was verified through simulations.
In the last few years, the Internet of Things (IoT) has become important part of our lives and its influence is expected to exponentially increase in the next years. Computer systems and applications are improved day by day and with the advancement in such area it gives birth to new cyber-attacks. Man in the Middle attacks (MITM) are one of those attacks. An attack where an outsider or third party enters in between two online users, where both of the users are unaware of it. Mainly it is knowing as a protocol to an unauthorized user within the system who can access as well as change the information of the system without leaving any trace to the existing users. Cloud, edge and fog computing added more flavors in terms of better throughput and low latency in ease of accessing data. Edge computing refers to a distributed open platform which helps off-loading tasks and processing of cloud at edge of the network. The edge serves as a bridge between the digital and physical worlds making gateways, systems and services smart and efficient. Due to the exponential growth of IoT produced data, its complexity is also expected to increase and raises need for innovation for improved security in Mobile Edge Computing (MEC) environment. This research is conducted to propose a lightweight Blockchain solution using private/ public keys and employing shading for off-loading computation intensive tasks at MEC. Inter-Planetary File System (IPFS) database has been used to offload computational task from edge servers. Proposed technique is implemented using Java Script and Node.JS and simulated through Visual Studio Code and results are compared with other lightweight encryption algorithms proposed for IoT.
For the ad hoc network topology is changeable: the network scale becomes larger, which leads to difficulty in network management and lack of efficiency; The diversity of network services (text, pictures, audio, video, etc.) leads to the dynamic occupation of channels by nodes, which easily affects the end-to-end delay and throughput of the network. This study proposes a dynamic distributed TDMA protocol using theoretical analysis and network simulation verification methods. The full connection matrix of nodes is used for distributed scheduling. The influence of TDMA slot allocation on service delay is analyzed in detail. The simulation results of end-to-end delay and throughput of the network are given in the simulation experiment. The simulation shows that this directional routing protocol has some improvements in reducing end-to-end delay, reducing average packet hops, improving channel space reuse rate, and increasing network capacity.
The wireless sensor network is widely used in the Internet of Things. As its core technology, the clustering routing algorithm effectively prolongs the network life cycle. An energy balance algorithm for heterogeneous wireless sensors based on bilevel decision and data distribution is proposed. Firstly, a more suitable cluster head is selected through the bilevel decision-making and competition mechanism. Secondly, A multi-objective decision-making strategy is used to synthesize multiple factors for data distribution. It can be seen from the simulation results that the routing algorithm has a great improvement in the network life cycle, energy utilization rate and data transmission.
During vehicle driving, many problems will occur in the communication process of VANET, including but not limited to node conflict management, time delay, time slot division management, etc. The Media Access Control (MAC) protocol is specifically responsible for solving these problems. The existing MAC protocol with fixed time slot allocation cannot solve the problems of excessive node conflicts and low packet reception rate when current traffic is high. When designing MAC protocol for VANET, we must consider the speed and dynamic distribution of nodes, which is also the key to optimize the protocol. In this paper, we propose a new TDMA protocol, called SMDP-MAC (Adaptive Slot Management MAC Protocol Based on Dynamic Parameters). This protocol is a new protocol that divides time slots according to vehicle dynamic parameters to solve conflict problems. SMDP-MAC manages the time slot in the vehicle channel access and maintenance phase according to the vehicle's GPS information, driving direction, speed and acceleration to reduce the collision probability. In the SMDP-MAC protocol, the frame is divided into multiple timeslots based on TDMA, the timeslots in the frame are divided into two timeslot sets according to the direction of travel, and then the channel access timeslot is divided and selected according to the dynamic parameters of each vehicle (including GPS information, vehicle speed and vehicle acceleration information). After the network enters a stable state, the time slot occupation of the vehicle will also be dynamically adjusted according to the vehicle position.This paper presents the analysis and simulation results under the highway scenario and verifies the effectiveness of SMDP-MAC protocol by comparing with VeMAC, BMA and ASMAC protocols.
KEYWORDS: Detection and tracking algorithms, Signal detection, Computer simulations, Matrices, Signal processing, Systems modeling, Modulation, Mobile communications
For uplink massive MIMO systems with hundreds of antennas at the base station, the Linear Minimum Mean Square Error (MMSE) signal detection algorithm is near optimal but involves matrix inversion with high complexity. In this paper, we proposed a low complexity detection algorithm in uplink large-scale MIMO based on Reactive Tabu Search (RTS) algorithm by using SOR iterative algorithm as the initial solution vector algorithm. The simulation result shows that it can reduce the computational complexity from ο(K3) to ο(K2), where K is the number of users. Under the premise of BER performance of the original algorithm, the simulation result shows that the performance of SOR-RTS method is always close to the original RTS algorithm.
This paper focuses on the design of flexible and wearable antennas using textile substrates for wireless/satellite based communication and control systems supporting Internet of Things (IoT). The same are based on on-body communication in Wireless body area network (WBANs). The antennas are designed using two different textile substrates i.e. Jeans and Polyester with εr of 1.7 and 2.8 respectively. The substrates are selected for the ease of wearability and the compact size of the designed antennas. The antennas are designed to operate in the C-Band (4-8 GHz) which is popular for satellite communications. The reason that a higher frequency band is selected is to overcome the congestion issues in the lower satellite frequency bands. Various simulation parameters like bandwidth, reflection coefficient (S11), 2D and 3D radiation patterns, directivity, gain and efficiency of both the antennas are compared and analysed. The maximum achieved gain, bandwidth and efficiency are 3.8dBi, 9.8GHz and 88.4 % for jeans substrate antenna and 3.1dBi, 6.7GHz and 77.5% for polyester substrate antenna respectively. The antennas are designed using Agilent Advance Design System simulator.
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