Increasingly, mobile devices equipped with 802.11n interfaces are being used for a wide variety of applications including bandwidth-intensive HD video streaming. Recent work has shown that 802.11n interfaces are power-hungry, so energy management is an important challenge. 802.11n implementations have additional power states relative to earlier generations of 802.11 technology, so energy management challenges for 802.11n are qualitatively different compared to that faced by prior work. In this paper, we describe the design and implementation of Snooze, an energy management technique for 802.11n which uses two novel and inter-dependent mechanisms: client micro-sleeps and antenna configuration management. In Snooze, the APmonitors traffic on the WLAN and directs client sleep times and durations as well as antenna configurations, without significantly affecting throughput or delay. Snooze achieves 30~85% energy-savings over CAM across workloads ranging from VoIP and video streaming to file downloads and chats.

Complex interference in static multihop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multihop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP), which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient. WCP assigns rates inversely proportional to the number of bottlenecks a flow passes through while remaining extremely easy to implement. An idealized version of WCPCap is max-min fair, whereas a practical implementation of the scheme achieves rates within 15% of the max-min optimal rates while still being distributed and amenable to real implementation.

In this paper, we explore a simple yet effective technique for explicitly allocating airtime to each active pair of communicating neighbors in a wireless neighborhood so that TCP starvation in a wireless mesh network is avoided. Our explicit allocation is efficient, redistributing unused airtime and also accounting for airtime rendered unusable by external interference. Our technique requires no modifications to TCP/IP and the 802.11 MAC, and is responsive to short flows, MAClayer auto rate adaptation, and other dynamics, as we demonstate in extensive experiments on two indoor testbeds. Despite its simplicity, the technique is on average within 12% of the max-min optimal allocation on several canonical topologies. 1.

Most sensor network research and software design has been guided by an architectural principle that permits multinode data fusion on small-form-factor, resource-poor nodes, or motes . While we were among the earliest promoters of this approach, through experience we found that this principle leads to fragile and unmanageable systems and explore an alternative. The Tenet architecture is motivated by the observation that future large-scale sensor network deployments will be tiered , consisting of motes in the lower tier and masters , relatively unconstrained 32-bit platform nodes, in the upper tier. Tenet constrains multinode fusion to the master tier while allowing motes to process locally-generated sensor data. This simplifies application development and allows mote-tier software to be reused. Applications running on masters task motes by composing task descriptions from a novel tasklet library. Our Tenet implementation also contains a robust and scalable networking subsystem for disseminating tasks and reliably delivering responses. We show that a Tenet pursuit-evasion application exhibits performance comparable to a mote-native implementation while being considerably more compact. We also present two real-world deployments of Tenet system: a structural vibration monitoring application at Vincent Thomas Bridge and an imaging-based habitat monitoring application at James Reserve, and show that tiered architecture scales network capacity and allows reliable delivery of high rate data. 1

Complex interference in static multi-hop wireless mesh networks can adversely affect transport protocol performance. Since TCP does not explicitly account for this, starvation and unfairness can result from the use of TCP over such networks. In this paper, we explore mechanisms for achieving fair and efficient congestion control for multi-hop wireless mesh networks. First, we design an AIMD-based rate-control protocol called Wireless Control Protocol (WCP) which recognizes that wireless congestion is a neighborhood phenomenon, not a node-local one, and appropriately reacts to such congestion. Second, we design a distributed rate controller that estimates the available capacity within each neighborhood, and divides this capacity to contending flows, a scheme we call Wireless Control Protocol with Capacity estimation (WCPCap). Using analysis, simulations, and real deployments, we find that our designs yield rates that are both fair and efficient, and achieve near optimal goodputs for all the topologies that we study. WCP achieves this level of performance while being extremely easy to implement. Moreover, WCPCap achieves the max-min rates for our topologies, while still being distributed and amenable to real implementation.

Most sensor network research and software design has been guided by an architectural principle that permits multi-node data fusion on small-form-factor, resource-poor nodes, or motes. We argue that this principle leads to fragile and unmanageable systems and explore an alternative. The Tenet architecture is motivated by the observation that future large-scale sensor network deployments will be tiered, consisting of motes in the lower tier and masters, relatively unconstrained 32-bit platform nodes, in the upper tier. Masters provide increased network capacity. Tenet constrains multi-node fusion to the master tier while allowing motes to process locally-generated sensor data. This simplifies application development and allows mote-tier software to be reused. Applications running on masters task motes by composing task descriptions from a novel tasklet library. Our Tenet implementation also contains a robust and scalable networking subsystem for disseminating tasks and reliably delivering responses. We show that a Tenet pursuit-evasion application exhibits performance comparable to a mote-native implementation while being considerably more compact.