Multi-Channel Scheduling for Fast Convergecast in Wireless Sensor Networks

We explore the following fundamental question - how fast can information be collected from a wireless sensor network? We consider a number of design parameters such as, power control, time and frequency scheduling, and routing. There are essentially two factors that hinder efficient data collection - interference and the half-duplex single-transceiver radios. We show that while power control helps in reducing the number of transmission slots to complete a convergecast under a single frequency channel, scheduling transmissions on different frequency channels is more efficient in mitigating the effects of interference (empirically, 6 channels suffice for most 100-node networks). With these observations, we define a receiver-based channel assignment problem, and prove it to be NP-complete on general graphs. We then introduce a greedy channel assignment algorithm that efficiently eliminates interference, and compare its performance with other existing schemes via simulations. Once the interference is completely eliminated, we show that with half-duplex single-transceiver radios the achievable schedule length is lower-bounded by max(2nk − 1,N), where nk is the maximum number of nodes on any subtree and N is the number of nodes in the network. We modify an existing distributed time slot assignment algorithm to achieve this bound when a suitable balanced routing scheme is employed. Through extensive simulations, we demonstrate that convergecast can be completed within up to 50% less time slots, in 100-node networks, using multiple channels as compared to that with single-channel communication. Finally, we also demonstrate further improvements that are possible when the sink is equipped with multiple transceivers or when there are multiple sinks to collect data

W-MAC: A Workload-Aware MAC Protocol for Heterogeneous Convergecast in Wireless Sensor Networks

The power consumption and latency of existing MAC protocols for wireless sensor networks (WSNs) are high in heterogeneous convergecast, where each sensor node generates different amounts of data in one convergecast operation. To solve this problem, we present W-MAC, a workload-aware MAC protocol for heterogeneous convergecast in WSNs. A subtree-based iterative cascading scheduling mechanism and a workload-aware time slice allocation mechanism are proposed to minimize the power consumption of nodes, while offering a low data latency. In addition, an efficient schedule adjustment mechanism is provided for adapting to data traffic variation and network topology change. Analytical and simulation results show that the proposed protocol provides a significant energy saving and latency reduction in heterogeneous convergecast, and can effectively support data aggregation to further improve the performance

Lower and upper bounds for deterministic convergecast with labeling schemes

In wireless networks, broadcast and convergecast are the two most used communication primitives. Broadcast instructs a specific sink (or root) node to send a message to each node in the network. Convergecast instructs each node in the network to send a message to the sink. Without labels, deterministic convergecast is impossible even in a three-nodes network. Therefore, networking solutions for convergecast are based on probabilistic approaches or use underlying probabilistic medium access protocols such as CSMA/CA or CSMA/CD. In this paper, we focus on deterministic convergecast algorithms enhanced with labeling schemes. We investigate two communication modes: half-duplex (nodes either transmit or receive but not both at the same time) and full-duplex (nodes can transmit and receive data at the same time). For these two modes we investigate time and labeling lower and upper bounds. Even though broadcast and convergecast are similar, we prove that, contrary to broadcast, deterministic convergecast cannot be solved with short labels for some topologies. That is, O(log(n)) bits are necessary to solve deterministically convergecast where n is the number of nodes in the network. We also prove that O(n) communication time slots is required. We provide solutions that are optimal in the worst case scenarios, in terms of labeling and communication

Optimal Time Data Gathering in Wireless Networks with Multidirectional Antennas

International audienceA Wireless Network consists of a large number of devices, deployed over a geographical area, and of a base station where data sensed by the devices are collected and accessed by the end users. In this paper we study algorithmic and complexity issues originating from the problem of data gathering in wireless networks. We give an algorithm to construct minimum makespan transmission schedules for data gathering under the following hypotheses: the communication graph G is a tree network, the transmissions in the network can interfere with each other up to distance m, where m ≥ 2, and no buffering is allowed at intermediate nodes. In the interesting case in which all nodes in the network have to deliver an arbitrary non-zero number of packets, we provide a closed formula for the makespan of the optimal gathering schedule. Additionally, we consider the problem of determining the computational complexity of data gathering in general graphs and show that the problem is NP-complete. On the positive side, we design a simple (1+2/m)-factor approximation algorithm for general networks

Secure Minimum Time Data Collection (SMTDC) protocol for wireless sensor networks

Recent work has shown that a mobile data collector moving along a predefined trajectory can improve the real-time data collection duration and efficiency in wireless sensor networks (WSN). Due to the fixed trajectory and limited communication range, data collection is conducted using a many-to-one communication pattern known as convergecast. However, because of the confidentiality concern of data being transmitted, security issues such as security key leakage, eavesdropping, and malicious attack raise significant challenges in minimizing the data collection time. To address this issue, we present the design and implementation of the Secure Minimum Time Data Collection (SMTDC) protocol, a tree formulated, and time-scheduled protocol for large scale, stationary, hardware-limited WSN. SMTDC can cooperate with many existing security communication frameworks. During the tree formation phase of SMTDC, we build well-balanced optimized trees that have the potential for minimum data collection time. We formulate our approach as an integer linear programming problem and solve it using linear relaxation based iterative rounding (LR-IR). During the time scheduling phase of SMTDC, we use a heuristic time-slot arrangement algorithm to solve the tree scheduling problem. The proposed algorithms and schemes are validated through simulation experiments using GUROBI solver and OMNET++ under realistic WSN topology. The result shows that SMTDC tree formation outperforms other algorithms in building a more effectively secure and load-balanced tree, and SMTDC scheduling significantly improves the data collection time over pre-generated tree topology