Maximizing the lifetime of a sensor network has been a subject of intensive study. However, much prior work defines the network lifetime as the time before the first data-generating sensor in the network runs out of energy or is not reachable to the sink due to network partition. The problem is that even though one sensor is out of operation, the rest of the network may well remain operational, with other sensors generating useful data and delivering those data to the sink. Hence, instead of just maximizing the time before the first sensor is out of operation, we should maximize the lifetime vector of the network, consisting of the lifetimes of all sensors, sorted in ascending order. For this problem, there exists only a centralized algorithm that solves a series of linear programming problems with high-order complexities. This paper proposes a fully distributed algorithm that runs iteratively. Each iteration produces a lifetime vector that is better than the vector produced by the previous iteration. Instead of giving the optimal result in one shot after lengthy computation, the proposed distributed algorithm has a result at any time, and the more time spent gives the better result. We show that when the algorithm stabilizes, its result produces the maximum lifetime vector. Furthermore, simulations demonstrate that the algorithm is able to converge rapidly toward the maximum lifetime vector with low overhead.

We demonstrate that CSMA/CA networks, including IEEE 802.11 networks, exhibit severe fairness problem in many scenarios, where some hosts obtain most of the channel's bandwidth while others starve. Most existing solutions require nodes to overhear transmissions made by contending nodes and, based on the overheard information, adjust local rates to achieve fairness among all contending links. Their underlying assumption is that transmissions made by contending nodes can be overheard. However, this assumption holds only when the transmission range is equal to the interference range, which is not true in reality. As our study reveals, the overhearing-based solutions, as well as several nonoverhearing AIMD solutions, cannot achieve MAC-layer fairness in various settings. We propose a new rate control protocol, called Proportional Increase Synchronized multiplicative Decrease (PISD). Without relying on overhearing, it provides fairness in CSMA/CA networks, particularly IEEE 802.11 networks, by using only local information and performing localized operations. It combines several novel rate control mechanisms, including synchronized multiplicative decrease, proportional increase, and background transmission. We prove that PISD converges and achieves (weighted) fairness. We further introduce Queue Spreading (QS) to achieve MAC-layer fairness when there are multiple contention groups, in which case PISD will fail.

End-to-end fairness in a sensor network ensures that data from each sensor has an equal (or weighted) chance to reach the sink. It eliminates the problem that data flows from sensors at some locations (close to the sink) obtain most network bandwidth, while flows from sensors at other locations (far away from the sink) are starved. Existing fairness solutions assume single-path routing, which reduces achievable throughput of the network. In this paper, we propose a multipath fairness solution (MFS) that achieves end-to-end fairness among competing flows through fully distributed operations. MFS is easy to implement, which is advantageous in a resource-scarce sensor network. More importantly, it achieves much higher network throughput and better fairness among the flows.

Wireless LANs have been densely deployed in many urban areas. Contention among nearby WLANs is location-sensitive, which makes some hosts much more capable than others to obtain the channel for their transmissions. Another reality is that wireless hosts use different transmission rates to communicate with the access points due to attenuation of their signals. We show that location-sensitive contention aggravates the throughput anomaly caused by different transmission rates. It can cause throughput degradation and host starvation. This paper studies the intriguing interaction between location-sensitive contention and time fairness across contending WLANs. Achieving time fairness across multiple WLANs is a very difficult problem because the hosts may perceive very different channel conditions and they may not be able to communicate and coordinate their operations due to the disparity between the interference range and the transmission range. In this paper, we design a MAC-layer time fairness solution based on two novel techniques: channel occupancy adaptation, which applies AIMD on the channel occupancy of each flow, and queue spreading, which ensures that all hosts and only those hosts in a saturated channel detect congestion and reduce their channel occupancies in response. We show that these two techniques together approximate the generic adaptation algorithm for proportional fairness.

Maximizing the operational lifetime of a sensor network is a critical problem in practice. Many prior works define the network's lifetime as the time before the first sensor in the network runs out of energy. However, when one sensor dies, the rest of the network can still work, as long as useful data generated by other sensors can reach the sink. More appropriately, we should maximize the lifetime vector of the network, consisting of the lifetimes of all sensors, sorted in ascending order. For this problem, there exists only a centralized algorithm that solves a series of linear programming problems with high-order complexities. This paper proposes a fully distributed progressive algorithm which iteratively produces a series of lifetime vectors, each better than the previous one. Instead of giving the optimal result in one shot after lengthy computation, the proposed distributed algorithm has a result at any time, and the more time spent gives the better result. We show that when the algorithm stabilizes, its result produces the maximum lifetime vector. Furthermore, simulations demonstrate that the algorithm is able to converge rapidly towards the maximum lifetime vector with low overhead.

A wireless mesh network (WMN) provides a flexible and low-cost solution for end users to connect to the Internet through its multi-hop infrastructure. For such a network to proliferate, a fundamental problem that must be solved is to ensure the fair allocation of network bandwidth to all participating parties. This paper proposes a cross-layer design for achieving end-to-end maxmin fairness in WMNs. At the network layer, it allocates maxmin shares of network capacity to end-to-end flows. At the MAC layer, it realizes the maxmin bandwidth allocation through a two-level packet scheduling algorithm. The proposed design is able to equalize the end-to-end bandwidth allocation to competing flows that share common bottlenecks, while fully utilizing the network capacity. Comparing with previous works, our solution has two advantages. It is based on the popular IEEE 802.11 DCF. It achieves far better fairness (or weighted fairness) among end-to-end flows.

In wireless sensor networks (WSNs), timeliness is one of the most challenging problems for critical applications. Caccamo et al. designed a collision-free real-time MAC protocol for sensor networks by adopting the "cellular structure" in traditional telecommunication networks. They assumed that sensors are organized into many rigid hexagon cells and a router node is at the center of each cell to transmit inter-cell packets. By exploiting FDMA and TDMA, transmission collisions are avoided and real-time guarantees are provided. However, we observe that for inter-cell communication, idle-slots caused by the TDMA-based scheduling will degrade the throughput and delay performance of the entire network, especially for some real applications in which data flows have traffic-direction partiality characteristics. In the worst case, five sixths of inter-cell bandwidth will be wasted. In this paper, we propose four idle-slot recycling algorithms to improve channel utilization. Simulation results show that our proposed algorithms can greatly increase network throughput and decrease packet transmission delay, while the collision-free and real-time qualities of Caccamo's protocol are still retained.

Following the huge commercial success of WLAN, multihop wireless networks are expected to lead in the next wave of deployment. Fundamental methods for traffic engineering must be developed to support diverse application requirements in these networks. This paper studies the problem of how to support weighted bandwidth allocation among all end-to-end flows in a multihop wireless network. Our goal is to enable the network to adapt the flow rates such that global maxmin can be achieved. Our approach is to transform the global maxmin objective into four local conditions and design a distributed rate adaptation protocol based on those local conditions. Comparing with the prior art, our protocol has a number of advantages. It is designed for the popular IEEE 802.11 DCF. It replaces per-flow queueing with per-destination queueing. It achieves far better fairness (or weighted fairness) among end-to-end flows.

Fine-level rate control, particularly meeting rate requirements and differentiating various types of end-to-end traffic, remains an open problem for multihop wireless networks. Traditionally, rate assurance in wired networks is achieved through resource reservation and admission control, which can be efficiently implemented since the bandwidth capacity of each communication link is known and the sender of a link has the information of all flows that compete for the bandwidth of the link. In a wireless network, however, the capacity of each wireless link can change unpredictably over time due to contention from nearby links and dynamic channel conditions. An end-to-end flow consumes available bandwidth not only at links on its route but also at all nearby contending links, which makes resource reservation extremely complicated. We believe fundamental differences require a fundamentally different paradigm shift in solutions. Is there a simpler alternative to resource reservation and admission control that is better suited for wireless network dynamics? In this paper, we propose a new adaptive rate control function based on two novel protocols, called dynamic weight adaptation with floor and ceiling and proportional packet scheduling, which together implement prioritized rate assurance and sophisticated bandwidth differentiation among all end-to-end flows in a multihop wireless network without resource reservation and admission control. The adaptive function achieves global rate control objectives in a fully distributed way using only localized operations.

We demonstrate that CSMA/CA networks, including IEEE 802.11 networks, exhibit severe fairness problem in many scenarios, where some hosts obtain most of the channel's bandwidth while others starve. Most existing solutions require nodes to overhear transmissions made by contending nodes and, based on the overheard information, adjust local rates to achieve fairness among all contending links. Their underlying assumption is that transmissions made by contending nodes can be overheard. However, this assumption holds only when the transmission range is equal to the carrier sensing range, which is not true in reality. As our study reveals, the overhearing-based solutions, as well as several non-overhearing AIMD solutions, cannot achieve MAC-layer fairness in various settings. We propose a new rate control protocol, called PISD (Proportional Increase Synchronized multiplicative Decrease). Without relying on overhearing, it provides fairness in CSMA/CA networks, particularly IEEE 802.11 networks, by using only local information and performing localized operations. It combines several novel rate control mechanisms, including synchronized multiplicative decrease, proportional increase, and background transmission. We prove that PISD converges and achieves (weighted) fairness.

Due to the open nature of a sensor network, it is relatively easy for an adversary to eavesdrop and trace packet movement in the network in order to capture the receiver physically. After studying the adversary's behavior patterns, we present countermeasures to this problem. We propose a locationprivacy routing protocol (LPR) that is easy to implement and provides path diversity. Combining with fake packet injection, LPR is able to minimize the traffic direction information that an adversary can retrieve from eavesdropping. By making the directions of both incoming and outgoing traffic at a sensor node uniformly distributed, the new defense system makes it very hard for an adversary to perform analysis on locally gathered information and infer the direction to which the receiver locates. We evaluate our defense system based on three criteria: delivery time, privacy protection strength, and energy cost. The simulation results show that LPR with fake packet injection is capable of providing strong protection for the receiveriquests location privacy. Under similar energy cost, the safe time of the receiver provided by LPR is much longer than other methods, including Phantom routing [1] and DEFP [2]. The performance of our system can be tuned through a few system parameters that determine the tradeoff between energy cost and the strength of location-privacy protection.

Due to the open nature of a sensor network, it is relatively easy for an adversary to eavesdrop and trace packet movement in the network in order to capture the receiver physically. After studying the adversary's behavior patterns, we present countermeasures to this problem. We propose a location-privacy routing protocol (LPR) that is easy to implement and provides path diversity. Combining with fake packet injection, LPR is able to minimize the traffic direction information that an adversary can retrieve from eavesdropping. By making the directions of both incoming and outgoing traffic at a sensor node uniformly distributed, the new defense system makes it very hard for an adversary to perform analysis on locally gathered information and infer the direction to which the receiver locates. We evaluate our defense system based on three criteria: delivery time, privacy protection strength, and energy cost. The simulation results show that LPR with fake packet injection is capable of providing strong protection for the receiver's location privacy. Under similar energy cost, the safe time of the receiver provided by LPR is much longer than other methods, including Phantom routing (Kamat et al., 2005) and DEFP (Deng et al., 2005). The performance of our system can be tuned through a couple of parameters that determine the tradeoff between energy cost and the strength of location-privacy protection.