Purushottam Kulkarni

Energy Harvesting Sensor Nodes: Survey and Implications

Sensor networks with battery-powered nodes can seldom simultaneously meet the design goals of lifetime, cost, sensing reliability and sensing and transmission coverage. Energy-harvesting, converting ambient energy to electrical energy, has emerged as an alternative to power sensor nodes. By exploiting recharge opportunities and tuning performance parameters based on current and expected energy levels, energy harvesting sensor nodes have the potential to address the conflicting design goals of lifetime and performance. This paper surveys various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications. The study also discusses the implications of recharge opportunities on sensor node operation and design of sensor network solutions.

SensEye : a multi-tier camera sensor network

This paper argues that a camera sensor network containing heterogeneous elements provides numerous benefits over traditional homogeneous sensor networks. We present the design and implementation of senseye---a multi-tier network of heterogeneous wireless nodes and cameras. To demonstrate its benefits, we implement a surveillance application using senseye comprising three tasks: object detection, recognition and tracking. We propose novel mechanisms for low-power low-latency detection, low-latency wakeups, efficient recognition and tracking. Our techniques show that a multi-tier sensor network can reconcile the traditionally conflicting systems goals of latency and energy-efficiency. An experimental evaluation of our prototype shows that, when compared to a single-tier prototype, our multi-tier senseye can achieve an order of magnitude reduction in energy usage while providing comparable surveillance accuracy.

Wolverine: Traffic and road condition estimation using smartphone sensors

Monitoring road and traffic conditions in a city is a problem widely studied. Several methods have been proposed towards addressing this problem. Several proposed techniques require dedicated hardware such as GPS devices and accelerometers in vehicles [7][15][8] or cameras on roadside and near traffic signals [13]. All such methods are expensive in terms of monetary cost and human effort required. We propose Wolverine - a non-intrusive method that uses sensors present on smartphones. We extend a prior study [12] to improve the algorithm based on using accelerometer, GPS and magnetometer sensor readings for traffic and road conditions detection. We are specifically interested in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road. We evaluate the effectiveness of the proposed method based on experiments conducted on the roads in Mumbai, with promising results.

The case for multi--tier camera sensor networks

In this position paper, we examine recent technology trends that have resulted in a broad spectrum of camera sensors, wireless radio technologies, and embedded sensor platforms with varying capabilities. We argue that future sensor applications will be hierarchical with multiple tiers, where each tier employs sensors with different characteristics. We argue that multi-tier networks are not only scalable, they offer a number of advantages over simpler, single-tier unimodal networks: lower cost, better coverage, higher functionality, and better reliability. However, the design of such mixed networks raises a number of new challenges that are not adequately addressed by current research. We discuss several of these challenges and illustrate how they can be addressed in the context of SensEye, a multi-tier video surveillance application that we are designing in our research group.

Cooperative leases: scalable consistency maintenance in content distribution networks

In this paper, we argue that cache consistency mechanisms designed for stand-alone proxies do not scale to the large number of proxies in a content distribution network and are not flexible enough to allow consistency guarantees to be tailored to object needs. To meet the twin challenges of scalability and flexibility, we introduce the notion of cooperative consistency along with a mechanism, called cooperative leases, to achieve it. By supporting Δ-consistency semantics and by using a single lease for multiple proxies, cooperative leases allows the notion of leases to be applied in a flexible, scalable manner to CDNs. Further, the approach employs application-level multicast to propagate server notifications to proxies in a scalable manner. We implement our approach in the Apache web server and the Squid proxy cache and demonstrate its efficacy using a detailed experimental evaluation. Our results show a factor of 2.5 reduction in server message overhead and a 20% reduction in server state space overhead when compared to original leases albeit at an increased inter-proxy communication overhead.

Singleton: system-wide page deduplication in virtual environments

We investigate memory-management in hypervisors and propose Singleton, a KVM-based system-wide page deduplication solution to increase memory usage efficiency. We address the problem of double-caching that occurs in KVM---the same disk blocks are cached at both the host(hypervisor) and the guest(VM) page caches. Singletons main components are identical-page sharing across guest virtual machines and an implementation of an exclusive-cache for the host and guest page cache hierarchy. We use and improve KSM--Kernel SamePage Merging to identify and share pages across guest virtual machines. We utilize guest memory-snapshots to scrub the host page cache and maintain a single copy of a page across the host and the guests. Singleton operates on a completely black-box assumption---we do not modify the guest or assume anything about its behaviour. We show that conventional operating system cache management techniques are sub-optimal for virtual environments, and how Singleton supplements and improves the existing Linux kernel memory-management mechanisms. Singleton is able to improve the utilization of the host cache by reducing its size(by upto an order of magnitude), and increasing the cache-hit ratio(by factor of 2x). This translates into better VM performance(40% faster I/O). Singletons unified page deduplication and host cache scrubbing is able to reclaim large amounts of memory and facilitates higher levels of memory overcommitment. The optimizations to page deduplication we have implemented keep the overhead down to less than 20% CPU utilization.

Affinity-Aware Modeling of CPU Usage for Provisioning Virtualized Applications

While virtualization-based systems become a reality, an important issue is that of virtual machine migration-enabled consolidation and dynamic resource provisioning. Mutually communicating virtual machines, as part of migration and consolidation strategies, may get colocated on the same physical machine or placed on different machines. In this work, we argue the need for network affinity-awareness not only in placement but also in resource provisioning for virtual machines. First, we empirically quantify the resource savings due to colocation of communicating virtual machines. We also discuss the increase in resource usage due to dispersion of previously colocated virtual machines. Next, we build models based on different resource-usage micro-benchmarks to predict the resource usages when transitioning from non-colocated placements to colocated placements and vice-versa. These resource usage prediction models are usable along-with consolidation and migration procedures to determine requirements of VMs in colocated and non colocated scenarios. Via extensive experimentation, we evaluate the applicability of our models for synthetic and benchmark application workloads. We find that the models have high prediction accuracy -- 90th percentile prediction error within 3\% absolute CPU usage for both synthetic and application workloads.

ACE in the Hole: Adaptive Contour Estimation Using Collaborating Mobile Sensors

This paper focuses on the use of mobile sensors to estimate contours in a field. In particular, we focus on strategies to estimate the contour with minimum latency and maximum precision. We propose a novel algorithm, ACE (adaptive contour estimation), that (a) estimates and exploits information regarding the gradients in the field to move towards the contour and (b) uses a spread component to surround the contour in order to optimize latency. While it is possible for sensors to spread as they approach the contour, it is crucial to judiciously determine when and how much to spread. Spreading too early or too much may result in increasing the latency or affecting the precision. ACE dynamically makes this decision using local sensor measurements, history of measurements as well as collaboration between sensors while adapting to different types of deployment, distance from the contour and shapes of the contour. We demonstrate that ACE, in the absence of energy constraints precisely determines the contour with a lower latency than when only gradients are used for movement or when the sensors spread out right from the start of estimation. Additionally, we show that ACE significantly improves precision of contour estimation in the presence of energy constraints. We also demonstrate a proof of concept implementation on a mobile robot testbed.

LiT MAC: addressing the challenges of effective voice communication in a low cost, low power wireless mesh network

In this work, we consider the goal of enabling a local voice communication system, within a village, using a low cost and low power wireless mesh network. The design of an appropriate MAC is a major challenge in this context. Towards this goal, we present LiT: a full-fledged TDMA-based MAC protocol for real-time applications over such networks. We showcase the practicality of such a system through implementation-based evaluation of LiT on an inexpensive, low power 802.15.4 platform. While there is plentiful literature on the use of TDMA for wireless mesh networks, a practical multi-hop TDMA system remains elusive. In this regard, LiT addresses several practical concerns. It has built-in support for time-synchronization, has a flexible interface with routing, and has a dynamic TDMA schedule dissemination mechanism. LiT is multi-channel capable and is centrally controlled. It achieves robustness in the face of wireless packet errors by making extensive use of soft-state mechanisms. With appropriate duty cycling, LiT can make nodes run for several weeks without power off the grid. Evaluation of LiT on outdoor testbed shows quick flow setup (latency < 1s), low packet delay (< 240ms) and negligible data path jitter (median 0ms), essential for real-time applications.

Scalable consistency maintenance in content distribution networks using cooperative leases

We argue that cache consistency mechanisms designed for stand-alone proxies do not scale to the large number of proxies in a content distribution network and are not flexible enough to allow consistency guarantees to be tailored to object needs. To meet the twin challenges of scalability and flexibility, we introduce the notion of cooperative consistency along with a mechanism, called cooperative leases, to achieve it. By supporting /spl Delta/-consistency semantics and by using a single lease for multiple proxies, cooperative leases allow the notion of leases to be applied in a flexible, scalable manner to CDNs. Further, the approach employs application-level multicast to propagate server notifications to proxies in a scalable manner. We implement our approach in the Apache Web server and the Squid proxy cache and demonstrate its efficacy using a detailed experimental evaluation. Our results show a factor of 2.5 reduction in server message overhead and a 20 percent reduction in server state space overhead when compared to original leases albeit at an increased interproxy communication overhead.