Advances in wireless charging technology give great new opportunities for extending the lifetime of a wireless sensor network (WSN) which is an important infrastructure of IoT. However, the existing greedy algorithms lacked learning from the experiences of energy dissipation trends. Unlike the existing studies, this article proposes a reinforcement learning approach, called reinforcement learning recharging (RLR), for mobile charger to learn the trends of WSNs, including the energy consumption of the sensors, the recharging cost as well as the coverage benefit, aiming to maximize the coverage contribution of the recharged WSN. The proposed RLR mainly consists of three modules, including sensor energy management (SEM), charger location update (CLP), and charger reinforcement learning (CRL) modules. In the SEM module, each sensor manages its energy and calculates its threshold for the recharging request in a distributed manner. The CLP module adopts the quorum system to ensure effective communication between sensors and the mobile charger. Meanwhile, the CRL module employs attraction rewards to reflect the coverage benefit and penalties of waiting time raised due to charger movement and recharging other sensors. As a result, the charger accumulates the learning experiences from the$Q$-Table such that it is able to execute the appropriate actions of charging or moving in a manner of state management. Performance results show that the proposed RLR outperforms the existing recharging mechanisms in terms of charging waiting time of sensors, the energy usage efficiency of the mobile charger, as well as the coverage contribution of the given sensor network.

In IEEE 802.16e networks, with the popularisation of multimedia services, multicast and unicast services can coexist in one mobile subscriber station (MSS). The mobile devices are generally powered by battery, which is limited in energy. Thus, power saving is an important issue to be considered for extending the lifetime of the MSSs. The authors have proposed a multicast services‐based scheduling (MSBS) algorithm that improves the energy efficiency of both unicast and multicast services, while satisfying the quality of service requirements of the MSSs in 802.16e wireless networks. MSBS schedules the packets in such a way that each packet is transmitted before its deadline and the energy consumed by the MSSs is reduced by minimising the number of state transitions by the MSSs. The simulation results show that MSBS can produce significant overall energy‐saving and prolonged lifetime as compared to other scheduling schemes in 802.16e wireless networks.

Recently, object tracking application of sensor networks has drawn significant attention of the researchers due to its wide application. However, most of these studies cannot deal with the trade-off between energy efficiency and accuracy of the tracking. In object tracking sensor networks (OTSNs), the movement of the object generally follows some definite patterns. The moving object location, arrival time, path are likely to hide some useful association rules, which can be excavated by applying suitable data mining algorithm. In this paper, we have proposed an object tracking scheme for OTSNs using data mining approach. We have improved the Apriori algorithm for mining association rules and made it applicable to the OTSNs. The data mining algorithm is applied to the past movement information of the object and useful association rules are excavated, which are then used to predict the next location of the object. Our scheme predicts the next location of the object more accurately and increases the network lifetime. Experimental results have been conducted to evaluate the performance of our proposed scheme for OTSNs and they show that our scheme outperforms the existing schemes in terms of energy efficiency and accuracy of tracking.

In this paper, an energy efficient data storage method for top-k query in wireless sensor networks is proposed. In the proposed method, the sensor network is divided into a number of grids and there is a grid head present at the center of each grid. Each grid head is assigned a definite sub-range of sensed data and the grid heads store only those sensed data within the assigned sub-range. Division of network into grids distributes the network traffic and reduces the traffic hotspot problem, which prolongs the network lifetime. The grids are assigned sub-ranges in a snake-like fashion so that minimum communication is required to query the top-k sensed data from the sensor network. We have proposed an energy efficient query algorithm to query the top-k value of sensed data. Experimental results show that our proposed method can prolong the lifetime of the sensor network as compared to the existing methods.

In wireless sensor network (WSN), much literature focuses on developing energy-efficient protocols. In addition, many papers propose data storage schemes but they do not take power saving into consideration. Hence, these data storage schemes cannot perform well based on energy-efficient protocols. Therefore, it is very critical to propose a data storage scheme to support energy-efficient mechanism. In this paper, we propose an energy-efficient data storage scheme in WSN. Our scheme adopts a grid-base architecture, in which each grid guarantees that two sensors will stay in active mode while the other sensors stay in sleep mode to save energy. Simulations have shown that our energy-efficient data storage scheme can reduce energy consumption.

Localisation is one of the most important issues in wireless sensor networks, because the location information is typically useful for coverage, deployment, routing, location service, target tracking and rescue operations in wireless sensor networks. The localisation protocols are classified into two categories: range-based protocol and range-free protocol. The range-based protocols employ distance or angle estimation techniques to achieve fine accuracy, which require the use of expensive hardwares. On the other hand, the range-free techniques depend on the contents of received messages to support coarse accuracy. This study describes mobile anchor positioning, a range-free localisation method, which makes use of the beacon packets of mobile anchor and the location packets of neighbour nodes to calculate the location of the nodes. The anchor node, which is equipped with global positioning system, broadcasts its coordinates to the sensor nodes as it moves through the network. As the sensor nodes collect enough beacons, they are able to calculate their locations locally.

Data-centric storage is an effective and important technique in wireless sensor networks. There are many attributes with range values in an event, so the sensor will need to use multi-dimensional range queries to retrieve data. In this paper, we propose a data storage and range query method for multi-dimensional attributes in wireless sensor networks. The main idea is to map multi-dimensional events to their corresponding range spaces and build an in-network distributed data structure to efficiently gather the data of multi-dimensional range queries. Our performance evaluation shows that our proposed scheme can reduce message cost and hotspot problems to achieve load balancing even when a vast number of the events and sensor nodes are present in a sensor network.

This paper handles the issues related to centralized scheduling in multi-channel WiMAX mesh network. We have used the clique partitioning approach for scheduling. The scheduling algorithm optimizes the length of the scheduling cycle, as well as the buffer size requirement of each node. If sufficient number of channels is present to avoid secondary interference in the network, the static channel assignment strategy is followed whereby each link is assigned a channel that remains fixed throughout the scheduling. If not, channels will be allocated dynamically, i.e., channels for links may change during scheduling. The simulation result shows that our scheduling algorithm minimizes the length of the schedule as well as requires unit buffer in case sufficient number of channels is available.

Wireless sensor networking (WSN) is an emerging technology that enables remote monitoring on a large scale. Data-centric storage is an effective and important technique in WSNs. Its function is to store sensed events according to their attribute values by mapping them to some nodes in order to avoid routing all the values outside the network and flooding the queries. There are many attributes with range values in an event, so the sensor will need to use multi-dimensional range queries to retrieve data. The authors propose a data storage and range query method for multi-dimensional attributes in WSNs. The main idea is to map multi-dimensional events to their corresponding range spaces and build an in-network distributed data structure to efficiently gather the data of multi-dimensional range queries. The performance evaluation shows that the proposed scheme can reduce message cost and hotspot problems to achieve load balancing even when a vast number of the events and sensor nodes are present in a sensor network.

This study proposes a novel multi-channel medium access control protocol for mobile ad hoc networks that enables nodes to transmit packets in distributed channels. In our protocol, the ad hoc traffic indication message window is divided into two windows. The first window is called the deciding channel window (DCW). Source and destination nodes can negotiate with each other in deciding a channel that can be used to compete for the final data channel in the DCW. The second window is called the exchanging packet window (EPW). Pair source and destination nodes can compete to obtain a channel to transfer packets in the EPW. This mechanism can distribute pair source and destination nodes to compete for a data channel. Hence, because of this, collisions can be avoided greatly and throughput can be increased. The simulation results show that our protocol successfully exploits the use of the bandwidth of multiple channels effectively.

In many data-centric storage techniques, each event type is stored at a corresponding hashed location. Most of them fail to deal with storage memory space due to high percentage of the load is assigned to a relatively small portion of the sensor nodes. These nodes could become a hotspot, both for communication and storage. In this paper, we propose a cover-up scheme for data-centric storage. The main idea is to generate a virtual coordinate for a storage node which is overload. The virtual coordinate will cover-up original coordinate of the storage node. Hence, GPSR routing algorithm will ignore the old storage node. Our scheme can spread storage into different sensor nodes. Simulations have shown that the cover-up scheme can reduce the energy consumption while there are a vast number of the events in sensor network or the network size is very large.

The most energy-wasting part of the MAC protocol for wireless sensor network is at the idling condition, therefore it is crucial for power saving to be able to turn off the signal transducer of the wireless network when the equipment is idling. PMAC allows sensors that did not transfer for a long period of time to quickly enter a dormant state, but this type of design requires precise time synchronization mechanism. To achieve time synchronization is a very energy-consuming and very expensive mechanism in the sensor network structure. Additionally, the exchange action with the neighboring pattern after each cycle, not only generates additional energy consumption for data transfer, but also accompanied by factors such as competition, collision and pattern exchange failure. We propose an asynchronous MAC protocol (AMAC) in this paper and expect to improve the problem of energy wasting and time synchronization due to sleeping schedule exchange under the PMAC basic protocol.

This paper considers the bandwidth reservation problem in a mobile ad hoc network (MANET) to support QoS (quality-of-service) routing. We approach this problem by assuming a common channel shared by all hosts under a TDMA (time division multiple access) channel model. Existing solutions have addressed this problem by assuming a stronger multi-antenna model, where the bandwidth of a link is independent of the transmitting/receiving activities of its neighboring links, or a less strong CDMA-over-TDMA channel model, where the use of a time slot on a link is only dependent on the status of its one-hop neighboring links. While more practical and less costly, using a TDMA model needs to face the challenge of radio interference problems. In this paper, we propose a new protocol that can reserve routes by addressing both the hidden-terminal and exposed-terminal problems. The protocol can conduct accurate bandwidth calculation while performing route discovery. Simulation results are presented to verify how this new protocol performs.

One way to broadcast a popular video is to use a number of dedicated channels, each responsible for broadcasting some portion of the video periodically in a predefined way. The stress on the channels can be alleviated, and new viewers do not have to wait long to start their playback. Many approaches falling in this category have been proposed. One such scheme that interests us is the fast broadcasting (FB) scheme, which can broadcast a video using k channels by incurring at most O(D/2/sup k/) waiting time on new-coming viewers, where D is the length of the video. We consider a set of videos, each being broadcast by the FB scheme. Since the demand levels on these videos may change with time, it is sometimes inevitable to change the numbers of channels assigned to some videos. We propose a novel seamless channel transition enhancement on top of the FB scheme to dynamically change the number of channels assigned to a video on-the-fly. Clients currently viewing this video will not experience any disruption because of the transition. A channel allocation scheme is also proposed based on the arrival rates of videos to minimize the average waiting experienced by all viewers. From the system manager's point of view, the enhancement will make the FB scheme more attractive.

One way to broadcast a popular video is to let multiple users share fewer channels. The stress on channel demand can be alleviated without sacrificing viewers' waiting time. One such scheme that interests us is the fast broadcasting (FB) scheme (Juhn et al., 1997, 1998), which can broadcast a popular video using k channels without keeping newcoming viewers waiting for more than O(D/2/sup k/) time, where D is the length of the video. In this paper, we propose two enhancements to the FB scheme. First, since the level of demand on a video may change by time, we show how to dynamically change the number of channels assigned to the video and seamlessly perform this transition. Clients currently viewing this video will not experience any disruption during the transition. Second, given a set of channels and a set of popular videos, we propose a scheme to assign these channels to the videos such that the average viewers' waiting time is minimal. From the system manager's point of view, these enhancements will make the FB scheme more attractive.