Cooperative Computing System for Heavy-Computation and Low-Latency Processing in Wireless Sensor Networks

Now days, wireless technology is one of the center of attention for users and researchers. Wireless network is a network having large number of sensor nodes and hence called as “Wireless Sensor Network (WSN)”. WSN monitors and senses the environment of targeted area. The sensor nodes in WSN transmit data to the base station depending on the application. These sensor nodes communicate with each other and routing is selected on the basis of routing protocols which are application specific. Based on network structure, routing protocols in WSN can be divided into two categories: flat routing, hierarchical or cluster based routing, location based routing. Out of these, hierarchical or cluster based routing is becoming an active branch of routing technology in WSN. To allow base station to receive unaltered or original data, routing protocol should be energy-efficient and secure. To fulfill this, Hierarchical or Cluster base routing protocol for WSN is the most energy-efficient among other routing protocols. Hence, in this paper, we present a survey on different hierarchical clustered routing techniques for WSN. We also present the key management schemes to provide security in WSN. Further we study and compare secure hierarchical routing protocols based on various criteria.

Recently, the technology of wireless sensor networks (WSNs) experiences a growing use in home automation or advanced industry infrastructure applications. Despite a strong interest of industries in this technology, key issues like miniaturization and security of WSN nodes has not been solved yet. State-of-the-art WSN nodes do not provide credible security nor satisfying configurability and miniaturized implementations. This publication deals with these limitations and presents a WSN node that provides security, configurability, and a miniaturized design. To show the sensor node feasibility, the WSN node is implemented within a smart home demonstrator. Additionally, a miniaturized pre-study WSN node design is presented using the novel embedded wafer level ball grid array (eWLB) packaging technology. Furthermore, an eWLB based WSN node design is proposed that further miniaturize the presented WSN node.

Profiling environmental parameter using a large number of spatially distributed wireless sensor network (WSN) NODEs is an extensive illustration of advanced modern technologies, but high power requirement for WSN NODEs limits the widespread deployment of these technologies. Currently, WSN NODEs are extensively powered up using batteries, but the battery has limitation of lifetime, power density, and environmental concerns. To overcome this issue, energy harvester (EH) is developed and presented in this paper. Solar-based EH has been identified as the most viable source of energy to be harvested for autonomous WSN NODEs. Besides, a novel chemical-based EH is reported as the potential secondary source for harvesting energy because of its uninterrupted availability. By integrating both solar-based EH and chemical-based EH, a hybrid energy harvester (HEH) is developed to power up WSN NODEs. Experimental results from the real-time deployment shows that, besides supporting the daily operation of WSN NODE and Router, the developed HEH is capable of producing a surplus of 971 mA·hr equivalent energy to be stored inside the storage for NODE and 528.24 mA·hr equivalent energy for Router, which is significantly enough for perpetual operation of autonomous WSN NODEs used in environmental parameter profiling.

Herein, an Internet of Things (IoT) system with remote reconfigurable wireless sensor network (WSN) nodes is presented and its application to measure group work activity in a classroom is discussed. This IoT system consists of wiki pages, bots, (defined as remotely controlled devices), gateways, and remotely reconfigurable WSN Nodes. The bots/gateways and WSN nodes of the IoT system are controlled by scripts written on wiki pages that are read by the bot/gateways, which then forward the commands contained in the scripts to the WSN nodes. Each WSN node then executes the commands, obtains the resulting sensor values, and then returns those values to the bot/gateways. The bot/gateways relay the values and write them onto the wiki page. Each WSN node is flexible and reconfigurable because its behavior can be changed by the script commands written onto the wiki page. Using this IoT system, we created a measurement system to evaluate activity levels of group work in a classroom. After developing the measurement system, we found it was possible to adjust the sampling rate for obtaining sensor values simply by rewriting the script on the wiki page without directly manipulating the WSN.

Wireless sensor networks (WSNs) consist of small nodes with sensing, computation, and wireless communications capabilities. Even in predominantly static sensor networks, it is possible to have a few mobile nodes. Mobility of nodes in WSNs adds a significant challenge. In this article we present a survey of state-of-the-art routing techniques in wireless ad hoc and sensor networks and highlight the advantages/disadvantages and performance issues of each routing technique. The aim is to identify routing protocols that will be able to support the mobility of sensor nodes in WSNs consisting of both static and mobile (mixed WSN) nodes. The article concludes by presenting an approach for such a routing protocol.

Data aggregation is an important process for wireless sensor networks (WSNs). The important aspects with WSNs are to increase the lifetime and to reserve the battery power of sensor nodes. The energy of nodes is mainly utilized in the process of sensing and transmitting the data. Clustering is one of the processes in which the total WSNs are divided into the form of groups and each group has a cluster head (CH) and advantage of doing this is decrease of energy consumption and reduce the data collision. The blockchain technology is utilized in WSN by so many ways for example security, data storing, node recovery etc. because the role of blocks in blockchain is same as the role of node in WSN. In this paper, we propose a cluster-based data aggregation framework for wireless sensor networks based on the blockchain technique. The proposed scheme is based on cluster head (CH) selection based on energy, and nodes communicate with each other via the shortest path. Further, the proposed scheme is also using the concept of blockchain technology for the purpose of maximum data storage. KeywordsWireless sensor networksLow energy adaptive clustering hierarchy (LEACH)Data aggregationCluster headBlockchainAnd Energy consumption

Wireless Sensor Networks (WSNs) is an evolving technology used in a diverse set of applications. WSN might be applied in isolated or hazard areas where it is hard and costly to reach the nodes. Maintaining the sensor nodes in WSN is generally a complex and difficult task especially when the size of the network is large. Energy maintenance of the sensor nodes is one of the challenging tasks in WSN. Supply energy for WSN using energy harvesting is a promising approach. It enables the sensor nodes to exploit the renewable ambient energy sources such as solar, temperature, sound and pressure to achieve a continual energy source. AODV is a routing protocol that was adopted by Zigbee for mesh network. However, not much work exists in literature that explores deeply the capabilities of AODV under energy harvesting. In this paper, extensive simulation experiments have been conducted using ns-3 to study the behavior of ADOV for energy-harvested and limited-battery WSN assuming total supply energy is the same for both approaches. We have compared AODV for both approaches using different performance metrics.

The protection of wireless sensor networks (WSN) against malware attacks is crucial. The paper discusses the issue of malware attacks in WSN, which are commonly used for monitoring and surveillance in various applications. Due to resource constraints, sensor nodes in WSN are vulnerable to malware attacks, which can spread rapidly and paralyze the network. The development of new technologies such as IoT, Industry 4.0 has increased the importance of WSN, and it has become essential to address the challenges posed by the resource‐constrained nature of sensor nodes and security concerns. In this paper, a model is considered with two exposed states to investigate the behaviour of malware spreading in WSN, and a SE 1 E 2 IR (Susceptible—Exposed State 1 ‐ Exposed State 2 ‐ Infectious—Recovered) model is proposed. The model is formulated as a system of differential equations, and its equilibrium and stability are examined. The basic reproduction number (R 0 ) is also calculated as a key parameter that characterizes the spread of malware in the network. This parameter helps to identify the conditions under which the network will remain malware‐free or when it will experience an outbreak of malware. The proposed model provides a mechanism for the earlier detection of malware occurrences in WSN, and also discusses the effect of connectivity and coverages on the propagation of malware in the network. The paper also includes a comparative study of the proposed model with existing models; extensive theoretical study and computation analysis are performed to validate the proposed model.

Wireless Sensor Network (WSN) suffers from different malware attacks. Several traditional approaches are proposed for detecting fault nodes in WSN. It is necessary to redistribute the nodes and detect the fault nodes while modifying the WSN parameters. Faults can occur in the nodes interrupting the continuous communication process of the nodes in the WSN. The main reason for a fault is also the induction of the energy drain in a node to the maximum possible level, failure of links in communicating nodes due to bandwidth constraints, and attacks induced by the malicious nodes. To solve this problems, Extended Finite State Machine based Fault Tolerance (EFSM_FT) in the WSN is used to detect the fault sensor nodes in the WSN. In this approach, called the finite state machine (FSM), state prompted is modified while a set of situations are true. Every node can be absolutely to be faulty or not establishing on the sensor node states. Using sensor energy, drop rate, forward sensor rate, sensor obtained rate, bandwidth, and transmission delay, this method finds the node with the fault. As a result, this approach accurately detects the faulty nodes in the WSN. The simulation outcomes illustrate the proposed method has a better fault detection ratio and minimizes the false negative ratio in the WSN.

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

Wireless Sensor Networking is an important area of research due to its wide and varied applications, especially in environmental monitoring and health monitoring. Battery-powered Wireless Sensor Networks (WSNs) face the problem of limited lifetime due to fast depletion of charge of typical batteries. The incorporation of energy harvesting in WSNs thus becomes crucial for extending the lifetime of battery-powered WSNs, while enhancing the network performance. The Medium Access Control (MAC) protocol has to be properly designed so as to ensure proper operation of the sensor nodes in WSNs with energy harvesting. This paper presents a MAC protocol for energy harvesting WSNs, based on IEEE 802.15.4 MAC, which takes into account the power consumption of the sensor nodes during operation and the battery discharge characteristics. This MAC protocol also employs duty cycle adaptation based on node energy.

Wireless sensor network (WSN) with several sensors is used to group measurements of certain physical quantities or environmental conditions, including sound, temperature, pressure, vibration, motion, or pollution, at various locations and ranges. In WSNs, several protocols address the issue of routing. Sensor nodes in WSN usually have limited energy resources and storage capacities. Therefore, the issue of energy usage in sensors and protocols is very important. This paper analyzes and compares the quality of service (QoS) performances of three important routing protocols of the mobile ad-hoc network (MANET) including Ad-hoc on-demand distance vector (AODV), dynamic source routing (DSR), and destination sequenced distance vector (DSDV), in a smart building case study. The QoS evaluation metrics include residual energy of nodes, instant throughput (IT), average throughput (AT), packet delivery ratio (PDR), packet loss ratio (PLR), and route discovery latency (RDL) based on IEEE 802.15.4 MAC protocol standard. The simulation is carried out using NS2, and the WSN has 16 fixed and 4 mobility nodes with different speeds and paths. The simulation results illustrate that average throughput in AODV is 1.985118 (kbps), however, the figures for DSR and DSDV are 1.977780 and 1.720700 (kbps), respectively. PDR, also, in DSR stands at 1.0, but the figures for AODV and DSDV are lower with the range of 0.999572 and 0.997930, respectively. Overall, The DSR protocol provides a better performance compared to AODV and DSDV routing protocols in terms of PLR and PDR. Also, AODV has better efficiency in RDL and AT compared to other assumed protocols.

According to recent researches, the wireless sensor networks (WSN) which consume low levels of energy become more and more popular nowadays, so the research trend of optimizing energy for WSNs is rapidly increasing. LoRa technology is a modulation technique that provides long-range transfer of information and low power consumes. Besides, LoRaWAN is a network protocol that optimized for battery-powered end devices. The LoRa and LoRaWAN can be considered a suitable candidate for WSNs, which can reduce power consumption and extend the communication range. In this paper, we studied adaptive mechanisms in the transmission parameters of the LoRa network and proposed an energy-optimized solution for the adaptive algorithm. This research not only introduced the reference hardware of a sensor node in WSNs but also conducted experiments on typical LoRa network infrastructure

The ability of wireless sensor network (WSN) can be observed in different fields like patient wearable monitoring, health applications, intruder detection, combat monitoring and battlefield surveillance in the last few years. In such applications, WSN contains a wide range of sensor nodes, which will monitor continuously, and passes the data to end-user through base station (BS) or sink node (SN). In such applications where users are unattended to replace the sensor node frequently, that indicates users can expect long-lasting of WSN. So in this paper, we concentrated on long-lasting of WSN, by minimizing the energy utilization of sensor node in WSN. So we are applying the clustering technique. So, clustering will minimize the energy usage of the sensor node, such that it will improve the lifetime of WSN. In this, we introduced our proposed protocol “Low Energy Utilization with Dynamic Cluster Head (LEU-DCH)” which reduces the energy consumption of sensor nodes. Besides, we also have shown the best way of selecting how many clusters we need.

The use of Internet of Things (IoT) is increasing rapidly. In most of the cases, wireless sensor network (WSN) takes the responsibility of communication between IoT devices. The deployment of secure communication for resource-constrained sensor nodes in WSN leads to a great challenge for the researchers. WSNs are deployed in remote areas in most of the applications with almost no possibility of recharging. This makes efficient energy usage a major criterion to be considered while designing security solutions in this field. To keep WSN in confidential and to provide guaranteed packet delivery, secure communication is essential. This paper has proposed a protocol, called SAVEER, which is used to prevent from both the internal and the external threats by using low-cost encryption technique with one-way hash chain-based authentication mechanism. The rolling ball approach is used to prevent the anti-void problem. The simulation results show that SAVEER provides better routing efficiency than existing protocols SEER, INSENS, and CASER.