Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individual nodes. These networks require robust wireless communication protocols that are energy efficient and provide low latency. We develop and analyze low-energy adaptive clustering hierarchy (LEACH), a protocol architecture for microsensor networks that combines the ideas of energy-efficient cluster-based routing and media access together with application-specific data aggregation to achieve good performance in terms of system lifetime, latency, and application-perceived quality. LEACH includes a new, distributed cluster formation technique that enables self-organization of large numbers of nodes, algorithms for adapting clusters and rotating cluster head positions to evenly distribute the energy load among all the nodes, and techniques to enable distributed signal processing to save communication resources. Our results show that LEACH can improve system lifetime by an order of magnitude compared with general-purpose multihop approaches.

/pdf/an-application-specific-protocol-architecture-for-wireless-1s7y9fiv40.pdf

An application-specific protocol architecture for wireless microsensor networks

Statistics for Spatial Data.

Advances in processor, memory and radio technology will enable small and cheap nodes capable of sensing, communication and computation. Networks of such nodes can coordinate to perform distributed sensing of environmental phenomena. In this paper, we explore the directed diffusion paradigm for such coordination. Directed diffusion is datacentric in that all communication is for named data. All nodes in a directed diffusion-based network are application-aware. This enables diffusion to achieve energy savings by selecting empirically good paths and by caching and processing data in-network. We explore and evaluate the use of directed diffusion for a simple remote-surveillance sensor network.

/pdf/directed-diffusion-a-scalable-and-robust-communication-4tsx5vxsas.pdf

Directed diffusion: a scalable and robust communication paradigm for sensor networks

Mobile ad hoc routing protocols allow nodes with wireless adaptors to communicate with one another without any pre-existing network infrastructure. Existing ad hoc routing protocols, while robust to rapidly changing network topology, assume the presence of a connected path from source to destination. Given power limitations, the advent of short-range wireless networks, and the wide physical conditions over which ad hoc networks must be deployed, in some scenarios it is likely that this assumption is invalid. In this work, we develop techniques to deliver messages in the case where there is never a connected path from source to destination or when a network partition exists at the time a message is originated. To this end, we introduce Epidemic Routing, where random pair-wise exchanges of messages among mobile hosts ensure eventual message delivery. The goals of Epidemic Routing are to: i) maximize message delivery rate, ii) minimize message latency, and iii) minimize the total resources consumed in message delivery. Through an implementation in the Monarch simulator, we show that Epidemic Routing achieves eventual delivery of 100% of messages with reasonable aggregate resource consumption in a number of interesting scenarios.

/pdf/epidemic-routing-for-partially-connected-ad-hoc-networks-s5rslcaiip.pdf

Epidemic routing for partially-connected ad hoc networks

http://www.csun.edu/~andrzej/COMP529-S05/papers/Mesh%20Networks%20Survey.pdf

Wireless mesh networks: a survey

Parallel discrete event simulation (PDES) techniques have not yet made a substantial impact on the network simulation community because of the need to recast the simulation models using a new set of tools. To address this problem, we present a case study in transparently parallelizing a widely used network simulator, called ns. The use of this parallel ns does not require the modeler to learn any new tools or complex PDES techniques. The paper describes our approach and design choices to build the parallel ns and presents preliminary performance results, which are very encouraging.

/pdf/parallel-execution-of-a-sequential-network-simulator-47yag7b79j.pdf

Parallel execution of a sequential network simulator

Multi-channel multi-radio architectures have been widely studied for 802.11-based wireless mesh networks to address the capacity problem due to wireless interference. They all utilize channel assignment algorithms that assume all channels and radio interfaces to be homogeneous. However, in practice, different channels exhibit different link qualities depending on the propagation environment for the same link. Different interfaces on the same node also exhibit link quality variations due to hardware differences and required antenna separations. We present a detailed measurement study of these variations using two mesh network testbeds in two different frequency bands --- 802.11g in 2.4GHz band and 802.11a in 5GHz band. We show that the variations are significant and `non-trivial' in the sense that the same channel does not perform well for all links in a network, or the same interface does not perform well for all interfaces it is paired up with for each link. We also show that using the channel-specific link quality information in a candidate channel assignment algorithm improves its performance more than 3 times on average.

Understanding Channel and Interface Heterogeneity in Multi-channel Multi-radio Wireless Mesh Networks

Enterprise wireless networks face significant challenges to deliver Quality-of-Experience (QoE) with the variety of mobile applications. One of the fundamental challenges is that the traditional definition of network capacity (often defined as throughput capacity) is not sufficient to reflect applications' requirements in wireless networks. In this paper, we propose to rethink the network capacity of wireless networks to better incorporate QoE. Specifically, we first propose a novel concept of an Experiential Capacity Region (ExCR) for wireless networks. ExCR is defined as a set of simultaneous application flows whose QoE requirements can be satisfied by the network. Next, we present the infrastructure based ExBox system that measures per-application QoE metrics and determines the ExCR for wireless networks to better serve a set of mobile application flows. In its core, ExBox employs light-weight machine learning techniques that are tailored for dynamic wireless environments. Through both large-scale simulations and extensive real-life experiments on WiFi and LTE networks, we show that ExBox delivers QoE in admission control decision with a precision of ≈ 0.8 - 0.9, even when clients experience diverse channel quality. Moreover, ExBox quickly adapts to changing network environments without much overhead.

https://dl.acm.org/doi/pdf/10.1145/2999572.2999597

ExBox: Experience Management Middlebox for Wireless Networks

Cellular data networks are experiencing a serious capacity crunch in the face of exponential increase in mobile data traffic volume. New traffic management techniques are needed to improve network and user perceived performance. In this work, we consider the existence of a higher-layer, agent-based scheduling system that could potentially delay scheduling of low priority flows at peak loads. The priorities are assumed to be user or application tagged, either automatically or manually. The general goal is to potentially move the low priority flows in time and space opportunistically to reduce the overall resource needs. We develop and evaluate two scheduling schemes - one based on a straightforward greedy method that requires real-time load monitoring and the other based on model-based estimation of traffic loads and subscriber mobility based on historical data. Simulation results using a large-scale cellular network trace data collected inside a nationwide network show the potential of these approaches in reducing base station resource requirements. This indirectly demonstrates that if providers can incentivize subscribers to tag certain flows as low priority, they can potentially accommodate a significant number of additional subscribers in the same network without expending any additional resource.

Opportunistic traffic scheduling in cellular data networks

We envision a future where every object in our living and working environment will carry one or more RF tags. Based on the backscattering tag-to-tag communication link, these RF tags will be connected in a network without the need for the central interrogating device. We present a novel tag architecture that enables estimation of the parameters of wireless tag-to-tag channel by a passive receiver. Sampling the received baseband signal at different reflecting phases at the backscattering tag enables estimation of amplitude and phase of the tag-to-tag channel. The low-power implementation of the channel estimator, after envelope detection, integrates amplification and filtering of the baseband signal that is followed by analog-to-digital conversion. The channel estimator, implemented in 65 nm CMOS technology, has sensitivity of −45 dBm at 2.5% modulation index and consumes 122 nW.

Samir R. Das

Papers

Parallel execution of a sequential network simulator

Understanding Channel and Interface Heterogeneity in Multi-channel Multi-radio Wireless Mesh Networks

ExBox: Experience Management Middlebox for Wireless Networks

Opportunistic traffic scheduling in cellular data networks

Passive Wireless Channel Estimation in RF Tag Network