In wireless sensor networks, different applications feature different requirements in terms of such performance metrics as sensing coverage and data reporting latency. In most applications, it is usually sufficient to provide a Desired Sensing Coverage (DSC) lower than full coverage at any instance with the guarantee that the whole area will eventually be covered within a specified delay bound. Due to the fact that these applications are also expected to run for longer periods of time and at the same time battery recharging and replacement are costly, energy consumption in wireless sensor networks should be minimized while achieving the application goals. In this article, we propose a novel framework for application-specific data gathering which exploits a trade-off between coverage and latency, thereby minimizing energy consumption and extending the network lifetime. The proposed energy-efficient, constant-time, randomized scheme, called Coverage-Adaptive raNdom SEnsor sElection (CANSEE), selects a subset of k sensors to report at each round so as to fulfill the application-specific requirement of desired sensing coverage and bounded latency, instead of always guaranteeing full coverage and minimum latency. We present a probabilistic model to estimate: (i) the connectivity of those selected k sensors and the number of additional sensors needed to guarantee connectivity; (ii) a lower bound on k in each round; and (iii) the probability of almost surely having k data reporters using the Chernoff bound. The immediate event detection capability achieved by the proposed CANSEE scheme is also analyzed to compare the performance of our framework with other data gathering schemes that allow 100% coverage. Simulation results demonstrate that our framework leads to a significant conservation of energy (and thus extended network lifetime) with a small trade-off between coverage and data reporting latency, yet providing the required data reporting capability.

Data forwarding schemes that use a single ACK-based retransmission mechanism are widely used to increase the packet delivery ratio in wireless sensor networks. However, these schemes may waste a considerable amount of energy for data transmissions, especially when the link quality is low for ACK transmissions. In this paper, we propose a novel multi-ACK-based data forwarding scheme to minimize the energy consumption for unnecessary data retransmissions. The next hop forwarder selection significantly affects the energy efficiency of communications. Hence, we also develop a new next hop forwarder selection metric, called effective energy consumption (EEC), which makes the proposed data forwarding scheme suitable for geographic routing protocols. Mathematical analysis and simulation results demonstrate that the proposed multi-ACK data forwarding scheme can save much energy and reduce the total amount of traffic load in the network. More specifically, the combination use of multi-ACK data forwarding and EEC metric increases the energy efficiency by 47.8% when node density is low, and 75.0% when node density is high, compared to the geographic forwarding protocols which use a well-known metric, PRR × Distance.

Existing wireless access (mobile) routers are commonly based on the network address and port translation (NAPT) technique which permits simultaneously sharing a subscriber's connection to the core network with multiple users. However, the NAPT architecturally makes the users invisible on the core network side, thus becoming a user-oriented connection-sharing technique. In this paper, we propose a novel service provider-oriented wireless broadband (Libra) unlicensed nomadic access relay station (WiNNERS) for helping WiBro network service providers to make their business more lucrative by accommodating unlicensed band users as subscribers into their network. The WiNNERS offers service providers the capability to directly manage each of the unlicensed band users at the core network side. This direct management allows the service providers to flexibly and simply handle QoS, access control, and billing for each unlicensed band user. In order to distinguish each of the unlicensed band users, the WiNNERS constructs a virtual tunnel from each user's terminal to the core network access control router (ACR) using connection identifier (CID) which is defined for service (traffic) flow management within the WiBro system. Consequently, our proposed service provider-oriented relay station can be included into the WiBro network system with minimum modifications.

Achievable energy conservation rate in wireless sensor networks can further be enhanced depending on application-specific requirements such as data reporting latency and sensing coverage area. In this paper, we propose a novel framework for energy-conserving data gathering which exploits a trade-off between coverage and data reporting latency. The ultimate goal is to extend the network lifetime by offering only the application/user-specific quality of service (e.g., sensing coverage) in each data reporting round using (approximately) k sensors. The selection of these k sensors is based on a geometric probability theory and a randomization technique with constant computational complexity. The selected k sensors form a data gathering tree (DGT) rooted at the data gathering point. To improve on energy-savings, only the sensors on the DGT are scheduled to remain active (with transceiver on) during a reporting round so that the DGT is used as a backbone to reach the data gathering point. We present a probabilistic model for estimating the connectivity of the selected k sensors and also a recursive algorithm which derives the number of additional sensors required to probabilistically guarantee the connectivity. The immediate data reporting capability of sensors is also analyzed since the group of active sensors forming a DGT (backbone) in each round may not be able to serve as a dominating set. Simulation results show that the proposed framework leads to a significant conservation of energy with a small trade-off.

We propose a novel energy-conserving data gathering strategy for wireless sensor networks. The proposed strategy is based on a trade-off between coverage and data reporting latency with an ultimate goal of maximizing the network's lifetime. The basic idea is to select in each round only a minimum of k sensors as data reporters which are sufficient for a desired sensing coverage given by the users or applications. Such a selection of the minimum data reporters also reduces the amount of traffic flow to the data gathering point in each round, and thus avoids network congestion as well as channel interference/contention. The proposed strategy includes three schemes for the minimum k-sensor selection. Using these schemes, we evaluate such fundamental issues as event detection integrity and data reporting latency, which can be critical in deploying the proposed data gathering strategy. Simulation results demonstrate that the average data reporting latency is hardly affected and the real-time event detection ratio is greater than 80% when the desired sensing coverage is at least 80%. It is also shown that the sensors can conserve a significant amount of energy with a small trade-off, and that the higher the network density, the higher is the energy conservation rate without any additional computation cost.

A high-density wireless sensor network can be deployed for specific information-gathering. In such a network, sensors need to route their sensed data to a base station, consuming highly-limited and unreplenishable energy resource. Hence, one of the most critical issues in designing sensor data gathering algorithms is to minimize the energy consumption for network longevity while meeting certain requirements given, such as delay constraints, which may vary depending on specific applications or environmental situations. We propose a novel two-phase clustering (TPC) scheme for energy-saving and delay-adaptive data gathering in wireless sensor networks. The proposed scheme partitions the network into clusters in phase I, each with a cluster head, forming a direct link between cluster member and cluster head. In phase II, each cluster member searches for a neighbor closer than the cluster head within the cluster to set up an energy-saving data relay link. The sensors use either the direct link or the data relay link for their sensed data forwarding depending on the requirements specified by the users or applications. Simulation results show that the TPC reduces average transmission distance by up to 75% with the help of data relay links when there is no delay constraint, implying that there is a significant amount of energy-savings in collecting sensed data.

Since the routing is the most energy-consuming operation in large wireless sensor networks, the routing mechanisms need to dynamically distribute the routing load to multiple sensors in order to maximize the number of live sensors during a given time unit. In this paper we propose a novel angle-based dynamic path construction (ADPC) scheme for routing load distribution with a goal of ultimately extending the network lifetime. The ADPC scheme dynamically constructs a routing path to the base station with the help of a set of routers extracted from local neighbors. The router set selection is based on an angle, called routing angle, which plays a key role in controlling the number of routers and the length of the routing path which influences the data delivery latency. Each such router is chosen as a next-hop based on its current routing service load, thus achieving the delay-aware and energy-conserving routing load distribution. Simulation experiments demonstrate that the ADPC scheme leads to a much lower rate of sensor failures and is able to control the data delivery latency as compared to a single (alternate) path routing scheme.

Many novel ideas have been proposed for designing multihop routing protocols in MANET (mobile ad hoc networks). Many of them adopt a method, called flooding, to discover a routing path. In order to increase the over-all routing performance and make optimum use of the limited resources, discovered routing paths need to be dynamically maintained to be continuously optimal in the highly dynamic network topology. However, the flooding is inappropriate for the dynamic route maintenance due to its significant inherent overhead. In this paper, we propose a nomadic control packet (NCP)-based dynamic route maintenance scheme for adaptive routing in MANET. The NCP travels through the network based on a random walk, and collects its stopovers as a traversal record for the purpose of dynamic route maintenance and efficient route discovery. The NCP probabilistically provides nodes with clues to routing path updates by using its traversal record. The nodes can find up-to-date and optimal (less-loaded and shorter) routing path information from the clues, thereby adapting to the dynamic network topology and traffic load conditions. The NCP-based dynamic route maintenance scheme can be easily applied to ad hoc on-demand routing protocols such as AODV and DSR with minimum modifications. In our simulation study we modified the AODV protocol to maintain routing paths using NCPs' traversal record. The simulation results show that the utilization of NCPs helps the routing protocol to notably reduce average end-to-end packet delay with the help of the increased route optimality and traffic congestion control.

In this paper, we propose a protocol, called asynchronous data delivery protocol (AD/sup 2/P), in multi-hop wireless networks for processing time-uncritical data which needs to be stored in or retrieved from a database in the Internet using the existing TCP-based applications.

The majority of the existing ad hoc wireless network routing protocols has a tendency to use the shortest single path from the source to the destination. However, in constantly changing topologies such as those in mobile ad hoc networks, the shortest single path is quite unstable for reachability and also for traffic load equilibrium. In this paper, we propose a novel scheme, called Applicative Indirect Routing (AIR), to control network traffic congestion and refine the route availability by coping with unreliable links quickly. The proposed scheme, acting as a proactive routing protocol, utilizes additional information about the neighbors shared (defined as proxies) by the sender and receiver to find ondemand an alternative for the original path with unreliable links. The additional bandwidth usage in AIR to obtain the information about shared neighbors is so minimal that the bandwidth availability for data packets is not significantly affected. In our scheme, it is possible for the nodes to dynamically reroute incoming packets into alternative paths so the packets will reach their destinations even when the ideal routing path fails. The conducted simulation experiments show that AIR leads to a much improved system performance in terms of packet delivery ratio, average end-to-end packet delay, and network reliability as compared with a conventional proactive protocol, namely Destination-Sequenced Distance Vector (DSDV). AIR is also a competitive protocol in terms of packet delivery ratio as compared with two existing reactive protocols; namely Ad hoc On Demand Distance Vector (AODV) and Dynamic Source Routing (DSR).