The Effective Sleep Scheduling in Wireless Opportunistic Networks

In opportunistic networks the communication opportunities (contacts) are intermittent and there is no need to establish an end-to-end link between the communication nodes. The enormous growth of nodes having access to the Internet, along the vast evolution of the Internet and the connectivity of objects and nodes, has evolved as Internet of Things (IoT). There are different issues for these networks. One of them is the selection of IoT nodes in order to carry out a task in opportunistic networks. In this work, we implement a Fuzzy-based System for IoT node selection in opportunistic networks. For our proposed system, we use four input parameters: Node’s Free Buffer Space (NFBS), Node’s Successful Delivery Ratio (NSDR), Node’s Battery Level (NBL), Node Contact Duration (NCD). The output parameter is Node Selection Decision (NSD). The results show that the proposed system makes a proper selection decision of IoT nodes in opportunistic networks. The IoT node selection is increased up to 17% and 40% by increasing NBL and NSDR, respectively.

How to shorten time delay and enhance delivery ratio is still an open problem in the study of opportunistic networks. Most proposals are trying to deal with this issue by introducing infrastructures. Although related research has been proven to be useful in improving the routing performance of the network, there is still room for further improvement. In this article, inspired by the powerful message synchronization capability of wireless sensor networks (WSNs), we propose a new opportunistic network framework called WON that introduces WSNs into opportunistic network. With the support of WSNs, fast message delivery and high success ratio can be achieved. We specifically present the layered architecture of WON and compare WON to existing architectures in opportunistic networking. The simulation results concerning delivery delay and success ratio are highly encouraging. Finally, open issues are outlined.

Designed as a specialized ad hoc network suitable for applications such as emergency responses, OppNets are considered as a sub-class of DTN where communication opportunities are intermittent, so an end-to-end path between the source and the destination may never exist. Existing networks have already brought connectivity to a broad range of devices, such as hand held devices, laptops, tablets, PC, etc. The Internet of Things (IoT) will extend the connectivity to devices beyond just mobile phones and laptops, but to buildings, wearable devices, cars, different things and objects. There are different issues for these networks. One of them is the selection of IoT nodes in order to carry out a task in opportunistic networks. In this work, we implement a Fuzzy-Based System for IoT node selection in opportunistic networks. For our proposed system, we use four input parameters: IoT Node’s Unique Encounters (NUE), IoT Node’s Free Buffer Space (NFBS), IoT Node’s Batter Level (NBL) and IoT Node Contact Duration (NCD). The output parameter is IoT Node Selection Decision (NSD). The results show that the proposed system makes a proper selection decision of IoT nodes in opportunistic networks. The IoT node selection is increased up to 25% and 11% by increasing NCD and NUE, respectively.

In opportunistic networks the communication opportunities (contacts) are intermittent and there is no need to establish an end-to-end link between the communication nodes. The enormous growth of devices having access to the Internet, along the vast evolution of the Internet and the connectivity of objects and devices, has evolved as Internet of Things (IoT). There are different issues for these networks. One of them is the selection of IoT devices in order to carry out a task in opportunistic networks. In this work, we implement a Fuzzy-Based System for IoT device selection in opportunistic networks. For our system, we use four input parameters: IoT Device’s Number of Past Encounters (IDNPE), IoT Contact Duration (IDCD), IoT Device Storage (IDST) and IoT Device Remaining Energy (IDRE). The output parameter is IoT Device Selection Decision (IDSD). The simulation results show that the proposed system makes a proper selection decision of IoT devices in opportunistic networks. The IoT device selection is increased up to 15% and 27% by increasing IDNPE and IDRE, respectively.

The Internet of Things (IoT) enhances the succeeding generation of web facilities by supporting pleasant relations among people and linked devices. A common way to connect IoT devices is to create an environment based on global infrastructure to create connections between objects, tasks, people, sensors, places, and machinery. Suitable organization of IoT-based structures in smart cities as well as societies based on channeling, treating, processing, sensing data, and faster communication systems for IoT devices. The crucial need for universal access and real-time performance induces the expedition for a network-based IoT substructure. Opportunistic networks and IoT are originally distributed computing standards. Aside from the circumstance that IoT and opportunistic networks are unrelated and measured separate independent communication sites, furthermore the paper proposes a novel opportunistic-IoT network (opportunistic network based on IoT’s qualities). In addition, it is stated that how we can create a well-defined opportunistic network through discovering essential connections among individuals and smart devices is one key issue between opportunistic societies. Because of these realities, the paper analyses a few basic applications, forthcoming challenges in the formation of opportunistic networks based on the IoT background, and the organization of opportunistic network’s forwarding procedures. The paper also implements, links, and evaluates the functionality of three forwarding protocols named PRoPHET, MaxProp, and Epidemic with a realistic city model by using THE ONE simulator.

Wireless Sensor Networks (WSNs) consist of a large number of small and low cost sensor nodes powered by small batteries and equipped with various sensing devices. Usually, for many applications, once a WSN is deployed, probably in an inhospitable terrain, it is expected to gather the required data for quite some time, say for years. Since each sensor node has limited energy, these nodes are usually put to sleep to conserve energy, and this helps to prolong the network lifetime. There are two major approaches to sleep scheduling of sensor nodes, viz. (i) random (ii) synchronized. Any sleep scheduling scheme has to ensure that data can always be routed from source to sink. In this paper, we propose a novel approach for sleep scheduling of sensor nodes using a tree and an energy aware routing protocol which is integrated with the proposed sleep scheduling scheme. The tree is rooted at the sink node. The internal nodes of the tree remain awake and the leaf nodes are made to sleep. This provides an assured path from any node to the sink node. The tree is periodically reconstructed considering the remaining energy of each node with a view to balance energy consumption of nodes, and remove any failed nodes from the tree. The proposed approach also considerably reduces average energy consumption rate of each node as we are able to put more number of nodes to sleep in comparison to other approaches. Additional fault-tolerance is provided by keeping two paths from each node towards the sink. Extensive simulation studies of the proposed routing protocol has been carried out using Castalia simulator, and its performance has been compared with that of a routing protocol, called GSP, which incorporates sleep scheduling using random approach. The simulation results show that the proposed approach has longer network lifetime in comparison to that provided by GSP, and the energy consumption of nodes is also balanced.

In the next generation Internet, it is expected that human, smart devices, and “things” will be able to communicate and interact with each other opportunistically in order to share their data. An analysis of this type of relationship is made possible due to the advent of the Opportunistic Internet of Things (OppIoT), a new paradigm that enable information sharing and dissemination among opportunistic communities formed based on human mobility and opportunistic contacts. Designing data dissemination and routing protocols for opportunistic IoT is a challenge since contacts between nodes and users’ social behaviors are to be tighten together as design constraints. Nonetheless, as opportunistic networking rely on spontaneous connectivity between the users and wireless devices, it can be argued that OppIoT is a form of opportunistic social networks (OppNets) extension, with focus on the relationship between human and opportunistic connection of smart things. As such, some routing protocols that have been designed to work for infrastructureless OppNets can also be applied in OppIoT systems. In this context, the History Based Routing Protocol for Opportunistic Networks (HiBOp) is an appealing choice. In this paper, an acknowledgement (ACK) forwarding mechanism to boost the performance of HiBOp is proposed based on the concept of centrality. Simulation results are provided, showing that HiBOp with centrality outperforms HiBOp in terms of predefined performance metrics.

Assessments on routing protocols for delay tolerant network (DTN) or opportunistic network considered various metrics such as delivery ratio, overhead and delay, but energy consumption as a metric is not well analyzed. Since the energy aspect is now an issue, routing protocols should be considered from an energy consumption point of view. In this article, some basic routing protocols of the opportunistic network analyzed from the energy aspect alongside other standard metrics. Afterward, the performance of each routing protocol for different situations assessed through network effective factors. Finally, the simulation results show that Spray and Wait algorithm has better energy performance compared to Epidemic and PRoPHET. Analyzing a protocol with a single-relay selection that minimizes the transmission energy and increase the energy efficiency of all devices in a wireless network. This technique is analyze the opportunistic relaying in the paradigm of D2D communication and study the opportunistic schemes with a single relay selection to minimize energy consumption of the devices in a wireless network. The fact is that The D2D communication ensures that the energy consumed for the data relaying is negligible and The D2D communication ensures that the selection of the relaying device exploits the diversity from neighboring devices in order to minimize the energy consumed by the devices for forwarding the data to the BS.

Usage of Internet of Things (IoT) devices are growing rapidly, resulting in the evolution of IoT infrastructure and efficient energy consumption. Organizations processing IoT big data in real-time for insights require various platforms that process high-velocity data to obtain incremental results. Streaming workflow applications designed consists of different data pipelines to support the decision-making process. These applications run on virtual machines provided by IaaS (Infrastructure as a Service) similar to the on-premise data center. The I/O operations performed by storage systems on these virtual machines result in considerable energy consumption. This paper calculates the energy consumption of storage systems during I/O operations of streaming applications.

WBANs offer a variety of medical applications and have received considerable attention in recent years. Due to the limited energy of sensors, prolonging network lifetime is of paramount importance for WBANs. Although duty-cycling techniques can conserve energy consumption and energy harvesting techniques can provide extra energy supply, the former leads to huge data delivery delay and the latter cannot supply energy infinitely and stably. Therefore, how to maximize network lifetime at low latency is still an open and challenging problem. In this article, we introduce a three-level sleep scheduling strategy for EH-WABNs. The first level is sensor node scheduling, which minimizes the number of sensors in an active sensor group. The second level is active sensor group discovery, which finds the maximum number of active sensor groups to enable alternate work in different frames to the greatest extent. The third level is active sensor group scheduling, which assigns an active sensor group in each frame. Importantly, this article provides a novel route to reduce energy consumption in EH-WBNAs, i.e. a combination of sensor sleep scheduling and energy harvesting, and we believe that this design can also be useful for other network scenarios.

The rapid development of the agricultural Internet of Things (IoT) is inseparable from the support of wireless sensor networks (WSNs) in recent years. To further facilitate the adaptation of WSNs to agricultural applications, reducing the energy consumption of sensor nodes in agricultural environments has become a crucial problem. Sleep scheduling in randomly deployed WSNs is an effective method to reduce the energy consumption of sensor nodes, which can extend the network lifetime while ensuring network coverage. However, most of the existing sleep scheduling algorithms require frequent information exchange (such as broadcasting to find neighboring nodes and collecting nodes’ residual energy), which will inevitably lead to massive energy consumption. To address this problem, in this article, an unmanned aerial vehicle (UAV)-assisted sleep scheduling algorithm (UAVSS) is proposed, which avoids excessive information exchange among nodes and ensures sufficient network coverage with the least number of sensor nodes. The UAV traverses all the sensor nodes along the shortest path to help information exchange and gather sensing data. Furthermore, the UAV path is planned by using the latest monarch butterfly optimization (MBO) algorithm. Simulation results indicate that the proposed UAVSS can prolong the network lifetime while ensuring the required area coverage.

Timely reliability modeling and evaluation of wireless sensor networks with adaptive N-policy sleep scheduling

An increasing number of mobile users (MUs) share common interests in general information, such as traffic information, weather forecast, and domestic/international news. However, the centralized infrastructure-based system has not been designed for efficiently disseminating the information of common interest (IoCI) to numerous requesters. Thanks to the rapid development of mobile devices equipped with large storage and multiple communication modes, opportunistic communication between a pair of MUs can be readily realized. With the aid of opportunistic networks formed by MUs, we can improve the connectivity of cellular networks in the rural areas, we can offload the tele-traffic from the overloaded cellular networks, and we can efficiently disseminate the IoCI in the densely populated areas. We commence with a detailed survey on the cross-disciplinary research area of social network analysis aided telecommunication networking. We continue by focusing our attention on the family of integrated cellular and large-scale opportunistic networks, whose performance is dominated by the inter-contact duration as well as the contact duration between any pairs of MUs. A continuous-time-pure-birth Markov chain is invoked for analyzing the relevant performance. We demonstrate that the delivery ratio of the IoCI before it expires becomes higher than 90% with the aid of opportunistic networks consisting of 20 MUs. Moreover, our experiments based on the InfoCom 2006 mobility trace show that the opportunistic networks are capable of offloading 58% of the tele-traffic from the cellular networks. Thereafter, we propose a hybrid information dissemination scheme for the integrated cellular and small-scale opportunistic networks, which is comprised of two main stages: 1) the base station-aided single-hop multicast (BSSHM) stage and 2) the cooperative multicast aided spontaneous dissemination stage. In contrast to their large-scale counterparts, in small-scale opportunistic networks, the information dissemination is mainly affected by the mobility of the MUs, by the wireless channel attenuation and by the resource scheduling, where a discrete-time-pure-birth Markov chain is utilized for characterizing the relevant performance. We demonstrate that our hybrid information dissemination scheme outperforms the traditional BSSHM in terms of various delay metrics, despite consuming less energy.

Internet of things (IoT) is a revolution of the internet where a group of computing devices, sensors, machines or people, having unique identifiers and the ability to transfer data over the network without human intervention, are interconnected. Opportunistic networks (OppNets) are a type of disruption‐tolerant networks, where network topology is not fixed and the devices are connected intermittently. Opportunistic IOT (OppIoT) is a blend of OppNets and IoT networks, where the data are shared among IoT devices and human communities exploiting the opportunistic contact nature of humans. The data is usually transmitted in a broadcast manner, exposing it to all the members of the network. Thus, securing the data transmitted is of utmost importance in OppIoT. This article proposes a trust‐based schemE (called T_CAFE) for securing the network against several attacks like sybil, bad mouthing, good mouthing, black hole and packet fabrication attacks. Using the opportunistic network environment simulator for performing simulations, it is found that the proposed T_CAFE protocol enhances the network security and outperforms routing protocols such as SHBPR, RSASec and ATDTN in terms of legitimate packet delivery, higher probability of message delivery, lower count of dropped messages and lower value of latency in packet delivery.

The realization of sustainable development depends on the efficient use of energy resources. Energy consumption productivity and efficiency are among important indices that play a critical role in explaining the behavior of energy consumption structure of different economic sectors, which in turn, plays a key role in policy making. From among economic sectors, the agriculture sector, as an important sector, depends on the consumption of energy as a factor underpinning agricultural production to a great extent. Thus, the present study tries to firstly calculate energy efficiency and productivity of agricultural sector, and then, investigate the relationship between production and energy consumption of New Zealand’s agricultural sector using simultaneous equations system and two-stage least squares method. The annual data of New Zealand agricultural economics are used for the period of 1990-2017. The results showed that agricultural sector’s energy consumption efficiency in New Zealand was mostly optimum according to energy efficiency index. In addition, estimation of energy equation revealed that the added value of agricultural sector had a positive influence on energy consumption growth. Among the other positively affecting variables, agricultural sector’s labour and energy consumption in the prior period could be mentioned. The negative sign of capital stock in the equation reflects the fact that the higher the investment in agricultural sector, the lower the energy consumption.