To raise the energy efficiency of wireless clients, it is important to sleep in idle periods. When multiple network applications are running concurrently on a single wireless client, packets of each application are sent and received independently, but multiplexed at MAC-level. This uncoordinated behavior makes it difficult to control of sleep timing. In addition, frequent state transitions between active and sleep modes consume non-negligible energy. In this paper, we propose a transport-layer approach that resolves this problem and so reduces energy consumed by multiple TCP flows on a wireless LAN (WLAN) client. The proposed method, called SCTP tunneling, has two key features: flow aggregation and burst transmission. It aggregates multiple TCP flows into a single SCTP association between a wireless client and an access point to control packet transmission and reception timing. Furthermore, to improve the sleep efficiency, SCTP tunneling reduces the number of state transitions by handling multiple packets in a bursty fashion. In this study, we construct a mathematical model of the energy consumed by SCTP tunneling to assess its energy efficiency. Through numerical examples, we show that the proposed method can reduce energy consumption by up to 69%.

Per-flow unfairness of TCP throughput in the IEEE 802.11 wireless LAN (WLAN) environment has been reported in past literature. A number of researchers have proposed various methods for alleviating the unfairness; most require modification of MAC protocols or queue management mechanisms in access points. However, the MAC protocols of access points are generally implemented at hardware level, so changing these protocols is costly. As the first contribution of this paper, we propose a transport-layer solution for alleviating unfairness among TCP flows, requiring a small modification to TCP congestion control mechanisms only on WLAN stations. In the past literature on fairness issues in the Internet flows, the performance of the proposed solutions for alleviating the unfairness has been evaluated separately from the network bandwidth utilization, meaning that they did not consider the trade-off relationships between fairness and bandwidth utilization. Therefore, as the second contribution of this paper, we introduce a novel performance metric for evaluating trade-off relationships between per-flow fairness and bandwidth utilization at the network bottleneck. We confirm the fundamental characteristics of the proposed method through simulation experiments and evaluate the performance of the proposed method through experiments in real WLAN environments. We show that the proposed method can achieve better a trade-off between fairness and bandwidth utilization, regardless of vendor implementations of wireless access points and wireless interface cards.

In this paper, we focus on two-layer wireless sensor networks (WSNs) that consist of sensor-concentrator and inter-concentrator networks. In order to collect as much data as possible from a wide area, improving of network capacity is essential because data collection applications often require to gather data within a limited period, i.e., acceptable collection delay. Therefore, we propose a two-stage scheduling method for inter-concentrator networks. The proposed method first strictly schedules time slots of links with heavy interference and congestion by exploiting the combination metric of interference and traffic demand. After that, it simply schedules time slots of the remaining sinks to mitigate complexity. Simulation-based evaluations show our proposal offers much larger capacity than conventional scheduling algorithms. In particular, our proposal improves up to 70% capacity compared with the conventional methods in situations where the proportion of one- and two-hop links is small.