Internet of Things (IoT) is an emerging technology that can be incorporated with wireless sensor networks (WSN) to extend its communication capabilities but the concept of WSN-IoT invites new challenges for the researchers as well as for the end users also. This paper investigates its applications for different domains (home/ industrial/ healthcare/ environment/ surveillance) and different issues associated with data acquisition /aggregation, optimal energy consumption and harvesting for smart devices and scalable communication etc.
Hazardous area, such as coal mines are below the earth surface. Below certain level there are dangerous and flammable gases. Unavailability of any mobile Network makes such area black spot for communication. In this paper, describe the using of LoRa that provide an wireless network upto certain range in this range using an another LoRa thatreceive and again retransmit the same data resulting in doubling the range of communication. Adding Lora repeaters multiply the range of communication. In such way routing sensor data till area where GPRS Packets are available and then upload the data to cloud. This can turn any black spot for communication reach to cloud storage.
The research paper is based on data acquisition of greenhouse monitoring systems and the issues to reduce its data latency and complexity. The paper contains the various parameters on which the data latency is dependent. Many of us faced similar issues in the transmission of data of greenhouse systems because of data congestion. Data Congestion reduces the data transmission speed which increases the delay. But with a proper understanding of delay parameters, Data latency effect, and Communication protocols the Data Congestion can be minimized and the system accuracy can be increased.
Enhancing security in wireless networks compromises quality of service (QoS) parameters, which reduces network scalability. In order to improve network security without compromising on QoS performance, redundant calculations must be reduced, which requires design of a performance tuning machine learning layer. Most of the research work done in this area of machine learning model design, focuses on reducing these redundancies via use of low complexity models, light weight mechanisms for trust evaluation, or simplifying key-exchange & other cryptographic processes. But these reductions in complexity also introduce security vulnerabilities into the system, for instance, using a light-weight trust model introduces trojan horse like attacks, while, using a low complexity cryptographic mechanism facilitates cryptanalysis. In order to reduce the computational complexity needed during security patch deployments, and improve overall quality of service (QoS) for wireless networks, this text proposes an augmented trust enabled QoS aware MAC model with intelligent blockchain sharding. The model works in 4 phases, wherein, initially an augmented trust model is implemented, which assists in improving QoS of network during routing. This is followed by design of a medium access control (MAC) model, which assists in further improving network QoS via an incremental learning layer that reduces packet contention, link quality issues, etc. Due to use of augmented trust layer, and incremental learning MAC model, various privacy & security loopholes are added to the network, which are handled via use of a proof-of-stake (PoS) consensus based blockchain model. The PoS model is very secure, has high traceability, but is moderately scalable, because of exponential relationship between number of blocks & computational complexity of mining. In order to reduce this complexity, and maintain a high QoS performance, this text proposes an intelligent blockchain sharding model that divides the underlying PoS blockchain into smaller shards, and manages each shard using tree-based hash range search model.
5G is emerging as a next-generation technology that enhances capacity, provides very low latency, very high data rates, and good quality of service. For any 5G device to operate successfully, the design and development of an antenna play a very important role. An antenna should be compact in size, cost-effective, and should cover the desired 5G band with enhanced bandwidth, gain, and negligible radiation losses. The shrinking size of the futuristic and next-generation wireless devices will need miniaturized and tightly assembled antennas without affecting the performance. With the number of antennas increased in the MIMO system it will be difficult to meet the space constraint of next-generation devices. Also, with the innovation and ever-increasing demand for flexible electronic devices, there will be a need to design flexible antennas for such devices. Flexible antennas are having tremendous applications in Gateways and Routers, Wireless Access Points, High-speed HD streaming, Handheld Devices, High-capacity MIMO networks for Public Transportation. This review paper explains the concept of flexible antennas and the various types of substrates used for antenna fabrication with its comparison. It also covers the various types of flexible MIMO antennas for 5G applications.
