Results 11 - 20
of
1,793
Energy-Efficient Computing for Wildlife Tracking: Design Tradeoffs and Early Experiences with ZebraNet
, 2002
"... Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The eld of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices ..."
Abstract
-
Cited by 719 (8 self)
- Add to MetaCart
(Show Context)
Over the past decade, mobile computing and wireless communication have become increasingly important drivers of many new computing applications. The eld of wireless sensor networks particularly focuses on applications involving autonomous use of compute, sensing, and wireless communication devices for both scienti c and commercial purposes. This paper examines the research decisions and design tradeos that arise when applying wireless peer-to-peer networking techniques in a mobile sensor network designed to support wildlife tracking for biology research.
Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks
- IEEE/ACM Transactions on Networking
, 2004
"... This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect senso ..."
Abstract
-
Cited by 702 (15 self)
- Add to MetaCart
(Show Context)
This paper proposes S-MAC, a medium access control (MAC) protocol designed for wireless sensor networks. Wireless sensor networks use battery-operated computing and sensing devices. A network of these devices will collaborate for a common application such as environmental monitoring. We expect sensor networks to be deployed in an ad hoc fashion, with nodes remaining largely inactive for long time, but becoming suddenly active when something is detected. These characteristics of sensor networks and applications motivate a MAC that is different from traditional wireless MACs such as IEEE 802.11 in several ways: energy conservation and self-configuration are primary goals, while per-node fairness and latency are less important. S-MAC uses a few novel techniques to reduce energy consumption and support self-configuration. It enables low-duty-cycle operation in a multihop network. Nodes form virtual clusters based on common sleep schedules to reduce control overhead and enable traffic-adaptive wake-up. S-MAC uses in-channel signaling to avoid overhearing unnecessary traffic. Finally, S-MAC applies message passing to reduce contention latency for applications that require in-network data processing. The paper presents measurement results of S-MAC performance on a sample sensor node, the UC Berkeley Mote, and reveals fundamental tradeoffs on energy, latency and throughput. Results show that S-MAC obtains significant energy savings compared with an 802.11-like MAC without sleeping.
Understanding packet delivery performance in dense wireless sensor networks
, 2003
"... Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery ..."
Abstract
-
Cited by 661 (15 self)
- Add to MetaCart
(Show Context)
Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance:the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks. In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments:an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks. Categories and Subject Descriptors C.2.1 [Network Architecture and Design]:Wireless communication; C.4 [Performance of Systems]:Performance
Tinydb: An acquisitional query processing system for sensor networks
- ACM Trans. Database Syst
, 2005
"... We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acq ..."
Abstract
-
Cited by 626 (8 self)
- Add to MetaCart
We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. Categories and Subject Descriptors: H.2.3 [Database Management]: Languages—Query languages; H.2.4 [Database Management]: Systems—Distributed databases; query processing
Establishing Pairwise Keys in Distributed Sensor Networks
, 2003
"... Pairwise key establishment is a fundamental security service in sensor networks; it enables sensor nodes to communicate securely with each other using cryptographic techniques. However, due to the resource constraints on sensors, it is infeasible to use traditional key management techniques such as ..."
Abstract
-
Cited by 543 (29 self)
- Add to MetaCart
Pairwise key establishment is a fundamental security service in sensor networks; it enables sensor nodes to communicate securely with each other using cryptographic techniques. However, due to the resource constraints on sensors, it is infeasible to use traditional key management techniques such as public key cryptography and key distribution center (KDC). To facilitate the study of novel pairwise key predistribution techniques, this paper presents a general framework for establishing pairwise keys between sensors on the basis of a polynomial-based key predistribution protocol [2]. This paper then presents two efficient instantiations of the general framework: a random subset assignment key predistribution scheme and a grid-based key predistribution scheme. The analysis in this paper indicates that these two schemes have a number of nice properties, including high probability (or guarantee) to establish pairwise keys, tolerance of node captures, and low communication overhead. Finally, this paper presents a technique to reduce the computation at sensors required by these schemes.
The design of an acquisitional query processor for sensor networks
- In SIGMOD
, 2003
"... We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acq ..."
Abstract
-
Cited by 523 (25 self)
- Add to MetaCart
(Show Context)
We discuss the design of an acquisitional query processor for data collection in sensor networks. Acquisitional issues are those that pertain to where, when, and how often data is physically acquired (sampled) and delivered to query processing operators. By focusing on the locations and costs of acquiring data, we are able to significantly reduce power consumption over traditional passive systems that assume the a priori existence of data. We discuss simple extensions to SQL for controlling data acquisition, and show how acquisitional issues influence query optimization, dissemination, and execution. We evaluate these issues in the context of TinyDB, a distributed query processor for smart sensor devices, and show how acquisitional techniques can provide significant reductions in power consumption on our sensor devices. 1.
Tinysec: A link layer security architecture for wireless sensor networks
- in Proc of the 2nd Int’l Conf on Embedded Networked Sensor Systems
"... We introduce TinySec, the first fully-implemented link layer security architecture for wireless sensor networks. In our design, we leverage recent lessons learned from design vulnerabilities in security protocols for other wireless networks such as 802.11b and GSM. Conventional security protocols te ..."
Abstract
-
Cited by 521 (0 self)
- Add to MetaCart
(Show Context)
We introduce TinySec, the first fully-implemented link layer security architecture for wireless sensor networks. In our design, we leverage recent lessons learned from design vulnerabilities in security protocols for other wireless networks such as 802.11b and GSM. Conventional security protocols tend to be conservative in their security guarantees, typically adding 16–32 bytes of overhead. With small memories, weak processors, limited energy, and 30 byte packets, sensor networks cannot afford this luxury. TinySec addresses these extreme resource constraints with careful design; we explore the tradeoffs among different cryptographic primitives and use the inherent sensor network limitations to our advantage when choosing parameters to find a sweet spot for security, packet overhead, and resource requirements. TinySec is portable to a variety of hardware and radio platforms. Our experimental results on a 36 node distributed sensor network application clearly demonstrate that software based link layer protocols are feasible and efficient, adding less than 10 % energy, latency, and bandwidth overhead.
Contiki - a Lightweight and Flexible Operating System for Tiny Networked Sensors
, 2004
"... of tiny networked devices that communicate untethered. For large scale networks it is important to be able to dynamically download code into the network. In this paper we present Contiki, a lightweight operating system with support for dynamic loading and replacement of individual programs and servi ..."
Abstract
-
Cited by 516 (45 self)
- Add to MetaCart
of tiny networked devices that communicate untethered. For large scale networks it is important to be able to dynamically download code into the network. In this paper we present Contiki, a lightweight operating system with support for dynamic loading and replacement of individual programs and services. Contiki is built around an event-driven kernel but provides optional preemptive multithreading that can be applied to individual processes. We show that dynamic loading and unloading is feasible in a resource constrained environment, while keeping the base system lightweight and compact.
Maté: A Tiny Virtual Machine for Sensor Networks
, 2002
"... Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu-late. ..."
Abstract
-
Cited by 510 (21 self)
- Add to MetaCart
Composed of tens of thousands of tiny devices with very limited resources ("motes"), sensor networks are subject to novel systems problems and constraints. The large number of motes in a sensor network means that there will often be some failing nodes; networks must be easy to repopu-late. Often there is no feasible method to recharge motes, so energy is a precious resource. Once deployed, a network must be reprogrammable although physically unreachable, and this reprogramming can be a significant energy cost. We present Maté, a tiny communication-centric virtual machine designed for sensor networks. Mat~'s high-level in-terface allows complex programs to be very short (under 100 bytes), reducing the energy cost of transmitting new programs. Code is broken up into small capsules of 24 instructions, which can self-replicate through the network. Packet sending and reception capsules enable the deploy-ment of ad-hoc routing and data aggregation algorithms. Maté's concise, high-level program representation simplifies programming and allows large networks to be frequently re-programmed in an energy-efficient manner; in addition, its safe execution environment suggests a use of virtual ma-chines to provide the user/kernel boundary on motes that have no hardware protection mechanisms.
The Cougar Approach to In-Network Query Processing in Sensor Networks
- SIGMOD Record
, 2002
"... The widespread distribution and availability of smallscale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such example is a sensor network consisting of a large number of sensor nodes that combine physical sensing capabilities such as te ..."
Abstract
-
Cited by 498 (1 self)
- Add to MetaCart
(Show Context)
The widespread distribution and availability of smallscale sensors, actuators, and embedded processors is transforming the physical world into a computing platform. One such example is a sensor network consisting of a large number of sensor nodes that combine physical sensing capabilities such as temperature, light, or seismic sensors with networking and computation capabilities. Applications range from environmental control, warehouse inventory, and health care to military environments. Existing sensor networks assume that the sensors are preprogrammed and send data to a central frontend where the data is aggregated and stored for offline querying and analysis. This approach has two major drawbacks. First, the user cannot change the behavior of the system on the fly. Second, conservation of battery power is a major design factor, but a central system cannot make use of in-network programming, which trades costly communication for cheap local computation.