Utilizing Path Diversity via Asynchronous and Asymmetric Wakeups in Sensor Networks

We present an asynchronous wakeup policy for wireless sensor networks that exploits the available path diversity for maximizing the expected network lifetime. We assume a random traffic generation model such that the rate is constant in time. Each node is assumed to have a set of forwarding neighbors, any of which may be used for forwarding its traffic to the sink. A node having data packet to send, transmits the packet to the first available node in its forwarding set. In order to maximize the network lifetime, we balance the power dissipation at the network nodes by adjusting the wakeup parameters at various nodes. Allowing different nodes to wakeup with different rates makes the scheme asymmetric. For ease of analysis, we restrict ourselves to static, open-loop policies. We show that the optimization problem is a Signomial Program (SP), that can be well approximated as a Geometric Program (GP). By extensive simulations, we compare the asymmetric policy thus obtained to the best possible symmetric policy obtained from the same optimization setup but ensuring additionally that the wakeup rates at all the nodes are the same (in which case the optimization problem is shown to be exactly a GP). The simulations show that allowing asymmetry can extend the network lifetime by effectively exploiting the available path diversity. Moreover, we also prove that, in case of symmetric policies, no piecewise static policy can beat the simple static policy that we use for comparison in our results. This shows that in the space of open-loop, asynchronous wakeup policies, employing the static, asymmetric policy presented in this paper is much more profitable than even the best piecewise static, symmetric policy.Research partially supported by the NSF under grant CNS-051955

Low Power, Low Delay: Opportunistic Routing meets Duty Cycling

Traditionally, routing in wireless sensor networks consists of two steps: First, the routing protocol selects a next hop, and, second, the MAC protocol waits for the intended destination to wake up and receive the data. This design makes it difficult to adapt to link dynamics and introduces delays while waiting for the next hop to wake up. In this paper we introduce ORW, a practical opportunistic routing scheme for wireless sensor networks. In a dutycycled setting, packets are addressed to sets of potential receivers and forwarded by the neighbor that wakes up first and successfully receives the packet. This reduces delay and energy consumption by utilizing all neighbors as potential forwarders. Furthermore, this increases resilience to wireless link dynamics by exploiting spatial diversity. Our results show that ORW reduces radio duty-cycles on average by 50% (up to 90% on individual nodes) and delays by 30% to 90% when compared to the state of the art

Providing efficient services for smartphone applications

Mobile applications are becoming an indispensable part of people\u27s lives, as they allow access to a broad range of services when users are on the go. We present our efforts towards enabling efficient mobile applications in smartphones. Our goal is to improve efficiency of the underlying services, which provide essential functionality to smartphone applications. In particular, we are interested in three fundamental services in smartphones: wireless communication service, power management service, and location reporting service.;For the wireless communication service, we focus on improving spectrum utilization efficiency for cognitive radio communications. We propose ETCH, a set of channel hopping based MAC layer protocols for communication rendezvous in cognitive radio communications. ETCH can fully utilize spectrum diversity in communication rendezvous by allowing all the rendezvous channels to be utilized at the same time.;For the power management service, we improve its efficiency from three different angles. The first angle is to reduce energy consumption of WiFi communications. We propose HoWiES, a system-for WiFi energy saving by utilizing low-power ZigBee radio. The second angle is to reduce energy consumption of web based smartphone applications. We propose CacheKeeper, which is a system-wide web caching service to eliminate unnecessary energy consumption caused by imperfect web caching in many smartphone applications. The third angle is from the perspective of smartphone CPUs. We found that existing CPU power models are ill-suited for modern multicore smartphone CPUs. We present a new approach of CPU power modeling for smartphones. This approach takes CPU idle power states into consideration, and can significantly improve power estimation accuracy and stability for multicore smartphones.;For the location reporting service, we aim to design an efficient location proof solution for mobile location based applications. We propose VProof, a lightweight and privacy-preserving location proof scheme that allows users to construct location proofs by simply extracting unforgeable information from the received packets

RF Integrated Circuits for Energy Autonomous Sensor Nodes.

The exponential growth in the semiconductor industry has enabled computers to pervade our everyday lives, and as we move forward many of these computers will have form factors much smaller than a typical laptop or smartphone. Sensor nodes will soon be deployed ubiquitously, capable of capturing information of their surrounding environment. The next step is to connect all these different nodes together into an entire interconnected system. This “Internet of Things” (IoT) vision has incredible potential to change our lives commercially, societally, and personally. The backbone of IoT is the wireless sensor node, many of which will operate under very rigorous energy constraints with small batteries or no batteries at all. It has been shown that in sensor nodes, radio communication is one of the biggest bottlenecks to ultra-low power design. This research explores ways to reduce energy consumption in radios for wireless sensor networks, allowing them to run off harvested energy, while maintaining qualities that will allow them to function in a real world, multi-user environment. Three different prototypes have been designed demonstrating these techniques. The first is a sensitivity-reduced nanowatt wake-up radio which allows a sensor node to actively listen for packets even when the rest of the node is asleep. CDMA codes and interference rejection reduce the potential for energy-costly false wake-ups. The second prototype is a full transceiver for a body-worn EKG sensor node. This transceiver is designed to have low instantaneous power and is able to receive 802.15.6 Wireless Body Area Network compliant packets. It uses asymmetric communication including a wake-up receiver based on the previous design, UWB transmitter and a communication receiver. The communication receiver has 10 physical channels to avoid interference and demodulates coherent packets which is uncommon for low power radios, but dictated by the 802.15.6 standard. The third prototype is a long range transceiver capable of >1km communication range in the 433MHz band and able to interface with an existing commercial radio. A digitally assisted baseband demodulator was designed which enables the ability to perform bit-level as well as packet-level duty cycling which increases the radio's energy efficiency.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110432/1/nerobert_1.pd

Evolutionary Approach to Efficient Provisioning and Self-organization in Wireless Sensor Networks (WSN)

Advances in low-power digital integration and microelectro-mechanical systems (MEMS) have paved the way for micro-sensors. These sensors are equipped with data processing capabilities along with sensory circuits. Sensor data are processed on these individual sensors and transmitted to the target (sink). Lowcost integration and small sizes of these sensors have generated special interest in the area of disposable-sensors and large scale platform management. Queries to these sensors are addressed to nodes which have data satisfying the same condition. However, these sensors may be constrained in energy, bandwidth, storage, and processing capabilities. Large number of such sensors along with these constraints creates a sensor-management problem. At the network layer it amounts to setting up the efficient route that transmits the non-redundant data from source to the sink in order to maximize one or more sensor objectives (e.g. battery (and sensor's) life, Sensor-Data yield). This is done while adapting to changing connectivity due to failure of some nodes and new nodes powering up. First part of the thesis propose a reduced-complexity genetic algorithm (GA) for optimization of multi-hop battery-constrained sensor networks. The goal of the system is to generate optimal number of sensor-clusters with cluster-heads. It results in minimization of the power consumption of the sensor system while maximizing the sensor objectives (coverage and exposure). The genetic algorithm is used to adaptively create various components such as cluster-members, cluster-heads, and next-cluster. These components are then used to evaluate the average fitness of the system based on the sequence of communication links towards the sink. We then enhance the genetic algorithm (GA) approach for secure deployment of resource constrained multi-hop sensor networks. The goal in this case is to achieve secure coverage and improve battery life by dynamically optimizing security attributes (Like authentication and encryption). Further, we augment the GA approach for intrusion detection of resource constrained multi-hop sensor networks. Traditional intrusion detection mechanisms have limited applicability to the sensor networks due to scarce battery and processing resources. Therefore, we propose an effective scheme that would offer a power efficient and lightweight approach to identify malicious attacks. We evaluate sensor node attributes by measuring the perceived threat and its suitability to host local monitoring node (LMN) that acts as trusted proxy agent for the sink and capable of securely monitoring its neighbors. Security attributes in conjunction with genetic algorithm jointly optimizes the selection of monitoring nodes (i.e., LMN) by dynamically evaluating node fitness by profiling workloads patterns, packet statistics, utilization data, battery status, and quality-of-service compliance. Second part of the thesis delves into application of Information Technology (and Industrial) Systems and devices where the use of sensor networks can deliver non-intrusive and effective telemetry for group-based server management. These systems (Like Data Centers or Shipment tracking) face major challenges in seamless integration of telemetry and control data that is essential to various autonomic management functions related to power, thermal, reliability, predictability, survivability, locality and adaptability. Such systems that are supported by a dense network of sense-points operating in noisy environment (Metals, Cables) are required to deliver reliable trends, measurements and analysis in a timely fashion. The traditional approaches to provide distributed observability and control using wired solutions are static, expensive, and nonscalable. We apply the proposed GA approach for this unique environment that replaces static wired sensors with dynamically reconfigurable battery-powered wireless sensors. The proposed technique employs machine learning approach to optimize sensor node function assignment, clustering decisions, route establishment and data collection trees for improved throughput that results in effective controls

Energy Efficient Servers

Computer scienc

Energy Efficient Servers

Computer scienc

Collaborative Traffic Offloading for Mobile Systems

Due to the popularity of smartphones and mobile streaming services, the growth of traffic volume in mobile networks is phenomenal. This leads to huge investment pressure on mobile operators' wireless access and core infrastructure, while the profits do not necessarily grow at the same pace. As a result, it is urgent to find a cost-effective solution that can scale to the ever increasing traffic volume generated by mobile systems. Among many visions, mobile traffic offloading is regarded as a promising mechanism by using complementary wireless communication technologies, such as WiFi, to offload data traffic away from the overloaded mobile networks. The current trend to equip mobile devices with an additional WiFi interface also supports this vision. This dissertation presents a novel collaborative architecture for mobile traffic offloading that can efficiently utilize the context and resources from networks and end systems. The main contributions include a network-assisted offloading framework, a collaborative system design for energy-aware offloading, and a software-defined networking (SDN) based offloading platform. Our work is the first in this domain to integrate energy and context awareness into mobile traffic offloading from an architectural perspective. We have conducted extensive measurements on mobile systems to identify hidden issues of traffic offloading in the operational networks. We implement the offloading protocol in the Linux kernel and develop our energy-aware offloading framework in C++ and Java on commodity machines and smartphones. Our prototype systems for mobile traffic offloading have been tested in a live environment. The experimental results suggest that our collaborative architecture is feasible and provides reasonable improvement in terms of energy saving and offloading efficiency. We further adopt the programmable paradigm of SDN to enhance the extensibility and deployability of our proposals. We release the SDN-based platform under open-source licenses to encourage future collaboration with research community and standards developing organizations. As one of the pioneering work, our research stresses the importance of collaboration in mobile traffic offloading. The lessons learned from our protocol design, system development, and network experiments shed light on future research and development in this domain.Yksi mobiiliverkkojen suurimmista haasteista liittyy liikennemäärien eksponentiaaliseen kasvuun. Tämä verkkoliikenteen kasvu johtuu pitkälti suosituista videopalveluista, kuten YouTube ja Netflix, jotka lähettävät liikkuvaa kuvaa verkon yli. Verkon lisääntynyt kuormitus vaatii investointeja verkon laajentamiseksi. On tärkeää löytää kustannustehokkaita tapoja välittää suuressa mittakaavassa sisältöä ilman mittavia infrastruktuuri-investointeja. Erilaisia liikennekuormien ohjausmenetelmiä on ehdotettu ratkaisuksi sisällönvälityksen tehostamiseen mobiiliverkoissa. Näissä ratkaisuissa hyödynnetään toisiaan tukevia langattomia teknologioita tiedonvälityksen tehostamiseen, esimerkiksi LTE-verkosta voidaan delegoida tiedonvälitystä WiFi-verkoille. Useimmissa kannettavissa laitteissa on tuki useammalle langattomalle tekniikalle, joten on luonnollista hyödyntää näiden tarjoamia mahdollisuuksia tiedonvälityksen tehostamisessa. Tässä väitöskirjassa tutkitaan liikennekuormien ohjauksen toimintaa ja mahdollisuuksia mobiiliverkoissa. Työssä esitetään uusi yhteistyöpohjainen liikennekuormien ohjausjärjestelmä, joka hyödyntää päätelaitteiden ja verkon tilannetietoa liikennekuormien optimoinnissa. Esitetty järjestelmä ja arkkitehtuuri on ensimmäinen, joka yhdistää energiankulutuksen ja kontekstitiedon liikennekuormien ohjaukseen. Väitöskirjan keskeisiä tuloksia ovat verkon tukema liikennekuormien ohjauskehikko, yhteistyöpohjainen energiatietoinen optimointiratkaisu sekä avoimen lähdekoodin SoftOffload-ratkaisu, joka mahdollistaa ohjelmistopohjaisen liikennekuormien ohjauksen. Esitettyjä järjestelmiä arvioidaan kokeellisesti kaupunkiympäristöissä älypuhelimia käyttäen. Työn tulokset mahdollistavat entistä energiatehokkaammat liikennekuormien ohjausratkaisut ja tarjoavat ideoita ja lähtökohtia tulevaan 5G kehitystyöhön