Daibo Liu

Duplicate detectable opportunistic forwarding in duty-cycled wireless sensor networks

Opportunistic routing, offering relatively efficient and adaptive forwarding in low-duty-cycled sensor networks, generally allows multiple nodes to forward the same packet simultaneously, especially in networks with intensive traffic. Uncoordinated transmissions often incur a number of duplicate packets, which are further forwarded in the network, occupy the limited network resource, and hinder the packet delivery performance. Existing solutions to this issue, e.g., overhearing or coordination based approaches, either cannot scale up with the system size, or suffer high control overhead. We present Duplicate-Detectable Opportunistic Forwarding (DOF), a duplicate-free opportunistic forwarding protocol for low-duty-cycled wireless sensor networks. DOF enables senders to obtain the information of all potential forwarders via a slotted acknowledgment scheme, so the data packets can be sent to the deterministic next-hop forwarder. Based on light-weight coordination, DOF explores the opportunities as many as possible and removes duplicate packets from the forwarding process. We implement DOF and evaluate its performance on an indoor testbed with 20 TelosB nodes. The experimental results show that DOF reduces the average duplicate ratio by 90%, compared to state-of-the-art opportunistic protocols, and achieves 61.5% enhancement in network yield and 51.4% saving in energy consumption.

DOF: Duplicate Detectable Opportunistic Forwarding in duty-cycled wireless sensor networks

Opportunistic routing, offering relatively efficient and adaptive forwarding in low-duty-cycled sensor networks, generally allows multiple nodes to forward the same packet simultaneously, especially in networks with intensive traffic. Uncoordinated transmissions often incur a number of duplicate packets, which are further forwarded in the network, occupy the limited network resource, and hinder the packet delivery performance. Existing solutions to this issue, e.g. overhearing or coordination based approaches, either cannot scale up with the system size, or suffers high control overhead. We present Duplicate-Detectable Opportunistic Forwarding (DOF), a duplicate free opportunistic forwarding protocol for low-duty-cycled wireless sensor networks. DOF enables senders to obtain the information of all potential forwarders via a slotted acknowledgement scheme, so the data packets can be sent to the deterministic next-hop forwarder. Based on light-weight coordination, DOF explores the opportunities as many as possible and removes duplicate packets from the forwarding process. We implement DOF and evaluate its performance on an indoor test-bed with 20 TelosB nodes. The experimental results show that DOF reduces the average duplicate ratio by 90%, compared to state-of-the-art opportunistic protocols, and achieves 61.5% enhancement in network yield and 51.4% saving in energy consumption.

RxLayer: adaptive retransmission layer for low power wireless

In large scale wireless sensor networks, retransmission strategies are widely adopted to guarantee the reliability of multi-hop forwarding. However, keeping retransmission over a bursty link may fail consecutively. Moreover, the retransmission will also be useless over those back-up links which are spatial correlated with the failed link. Thus, it is necessary to design an unified retransmission strategy, which considers both temporal and spacial link properties, to further improve network reliability and efficiency. In this paper, we propose RxLayer, a practical and general supporting layer of data retransmission. Without inducing noticeable overhead, RxLayer captures the temporal and spatial link properties by conditional probability models. A sender will retransmit data over the candidate link with the highest delivery probability while failures occur. RxLayer can be transparently integrated with most of the existing forwarding protocols. We implement RxLayer and evaluate it on both indoor and outdoor testbeds. The results show that RxLayer improves networks reliability and energy efficiency in various scenarios. The network reliability is improved by up to 7.82%, and the total number of transmissions is reduced by up to 36.3%.

Tele Adjusting: Using Path Coding and Opportunistic Forwarding for Remote Control in WSNs

On-air access of individual sensor node (called remote control) is an indispensable function in operational wireless sensor networks, for purposes like network management and real-time information delivery. To realize reliable and efficient remote control in a wireless sensor network (WSN), however, is extremely challenging, due to the stringent resource constraints and intrinsically unrealizable wireless communication. In this paper, we propose TeleAdjusting, a ready-to-use protocol to remotely control any individual node in a WSN. We develop a coding scheme for addressing on the cost-optimal reverse routing tree. In the address of each node, all its upstream relaying nodes are implicitly encoded. Then through a distributed prefix matching process between the local address and the destination address, a packet used for remote control is forwarded along a cost-optimal path. Moreover, TeleAdjusting incorporates opportunistic forwarding into the addressing process, so as to improve the network performance in terms of reliability and energy efficiency. We implement TeleAdjusting with TinyOS and evaluate its performance through extensive simulations and experiments. The results demonstrate that compared to the existing protocols, TeleAdjusting can provide high performance of remote control, which is as reliable as network-wide flooding and much more efficient than remote control through a pre-determined path.

CD-MAC: A contention detectable MAC for low duty-cycled wireless sensor networks

The energy efficiency and delivery robustness are two critical issues for low duty cycled wireless sensor networks. The asynchronous receiver-initiated duty cycling media access control (MAC) protocols have shown the effectiveness through various studies. In receiver-initiated MACs, packet transmission is triggered by the probe of receiver. However, it suffers from the performance degradation incurred by packet collision, especially under bursty traffic. Several protocols have been proposed to address this problem, but their performance is restricted by the unnecessary backoff time and long negotiation process. In this paper, we present Contention Detectable MAC (CD-MAC), an energy efficient and robust duty-cycled MAC for general wireless sensor network applications. By exploring the temporal diversity of the acknowledgements, a receiver recognizes the potential senders and subsequently polls individual senders one by one. We further design efficient algorithm to avoid the possible acknowledgement collision. We implement CD-MAC in TinyOS and evaluate the performance on an indoor testbed with single-hop and multi-hop networks. The results show that CD-MAC can significantly improve throughput by 1.72 times compared with the state-of-the-art receiver-initiated MAC protocol under bursty traffic loads. The results also demonstrate that CD-MAC can effectively mitigate the influence of hidden terminal problem and adapt to network dynamics well.

COF: Exploiting Concurrency for Low Power Opportunistic Forwarding

Due to the constraint of energy resource, the radio of sensor nodes usually works in a duty-cycled mode. Since the sleep schedules of nodes are unsynchronized, a sender has to send preambles to coordinate with its receiver(s). In such contexts, opportunistic forwarding, which takes the earliest forwarding opportunity instead of a deterministic forwarder, shows great advantage in utilizing channel resource. The multiple forwarding choices with temporal and spatial diversity increase the chance of collision tolerance in concurrent transmissions, potentially enhancing end-to-end network performance. However, the current channel contention mechanism based on collision avoidance is too conservative to exploit concurrency. To address this problem, we propose COF, a practical protocol to exploit the potential Concurrency for low power Opportunistic Forwarding. COF determines whether a node should concurrently transmit or not, by incorporating: (1) a distributed and light-weight link quality measurement scheme for concurrent transmission and (2) a synthetic method to estimate the benefit of potential concurrency opportunity. COF can be easily integrated into the conventional unsynchronized sender-initiated protocols. We evaluate COF on a 40-node testbed. The results show that COF can reduce the end-to-end delay by up to 41% and energy consumption by 18.9%, compared with the state-of-the-art opportunistic forwarding protocol.

Furion: Towards Energy-Efficient WiFi Offloading under Link Dynamics

Offloading network traffic from cellular to WiFi is widely used to reduce energy consumption since WiFi is assumed to have lower power consumption than cellular. However, we find that WiFi link quality may vary significantly under user mobility. Consequently, the energy efficiency of WiFi varies and sometimes becomes even worse than that of cellular. Therefore, widely used WiFi offloading may not be beneficial or even incurs more energy consumption. To address this issue, we propose Furion, an energy efficient WiFi offloading scheme that exploits beneficial WiFi links on smartphones. Towards such a goal, we investigate the relationship between energy efficiency and link quality. Accordingly, we propose a practical probabilistic model to predict WiFi energy efficiency based on the dynamics of link quality. We further extend the method to different environments by exploiting contextual factors in the prediction model to improve the accuracy. Based on the model, we design an adaptive offloading scheme to optimize the energy efficiency of WiFi offloading, while also guaranteeing user experience. We have implemented Furion on the Android platform and conduct extensive real-world experiments. The results demonstrate that Furion achieves 34.13% improvement in energy efficiency compared with the state-of-the- arts.

Frame counter: achieving accurate and real-time link estimation in low power wireless sensor networks

Link estimation is a fundamental component of forwarding protocols in wireless sensor networks. In low power forwarding, however, the asynchronous nature of widely adopted duty-cycled radio control brings new challenges to achieve accurate and real- time estimation. First, the repeatedly transmitted frames (called wake-up frame) increase the complexity of accurate statistic, especially with bursty channel contention and coexistent interference. Second, frequent update of every link status exhausts the limited energy supply due to long duration of beacon broadcast. In this paper, we propose meter (Distributed Frame Counter), which takes the opportunities of link overhearing to update link status in real time. Furthermore, meter does not only depend on counting the successfully decoded wake-up frames, but also counts the corrupted ones by exploiting the feasibility of ZigBee identification based on short-term sequence of the received signal strength. We implement meter in TinyOS and further evaluate the performance through extensive experiments on indoor and outdoor testbeds. The results demonstrate that meter can significantly improve the performance of the state-of-the-art link estimation schemes.

Chase : Taming Concurrent Broadcast for Flooding in Asynchronous Duty Cycle Networks

Asynchronous duty cycle is widely used for energy constraint wireless nodes to save energy. The basic flooding service in asynchronous duty cycle networks, however, is still far from efficient due to severe packet collisions and contentions. We present Chase, an efficient and fully distributed concurrent broadcast layer for flooding in asynchronous duty cycle networks. The main idea of Chase is to meet the strict signal time and strength requirements (e.g., Capture Effect) for concurrent broadcast while reducing contentions and collisions. We propose a distributed random inter-preamble packet interval adjustment approach to constructively satisfy the requirements. Even when requirements cannot be satisfied due to physical constraints (e.g., the difference of signal strength is less than a 3 dB), we propose a lightweight signal pattern recognition-based approach to identify such a circumstance and extend radio-on time for packet delivery. We implement Chase in TinyOS with TelosB nodes and extensively evaluate its performance. The implementation does not have any specific requirement on the hardware and can be easily extended to other platforms. The evaluation results also show that Chase can significantly improve flooding efficiency in asynchronous duty cycle networks.

Chase: Taming concurrent broadcast for flooding in asynchronous duty cycle networks

Asynchronous duty cycle is widely used for energy constraint wireless nodes to save energy. The basic flooding service in asynchronous duty cycle networks, however, is still far from efficient due to severe packet collisions and contentions. We present Chase, an efficient and fully distributed concurrent broadcast layer for flooding in asynchronous duty cycle networks. The main idea of Chase is to meet the strict signal timing and strength requirements (e.g., Capture Effect) for concurrent transmission while reducing contentions and collisions. We propose a distributed random inter-preamble packet interval adjustment approach to constructively satisfy the requirements. Even when requirements cannot be satisfied due to physical constraints (e.g., the difference of signal strength is less than a 3 dB), we propose a light-weight signal pattern recognition based approach to identify such a circumstance and extend radio-on time for packet delivery. We implement Chase in TinyOS and TelosB platform and extensively evaluate its performance. The implementation does not have any specific requirement on the hardware and can be easily extended to other platforms. The evaluation results also show that Chase can significantly improve flooding efficiency in asynchronous duty cycle networks.