Wireless energy transfer has recently emerged as a promising alternative to realize the vision of perpetual embedded sensing. However, this technology transforms the notion of energy from merely a node’s local commodity to, similarly to data, a deployment-wide shareable resource. The challenges of managing a shareable energy resource are much more complicated and radically different from the research of the past decade: Besides energy-efficient operation of individual devices, we also need to optimize networkwide energy distribution. To counteract these challenges, we propose an energy stack , a layered software model for energy management in future transiently powered embedded networks. An initial specification of the energy stack, which is based on the historically successful layered approach for data networking, consists of three layers: (i) the transfer layer, which deals with the physical transfer of energy; (ii) the scheduling layer, which optimizes energy distribution over a single hop; and (iii) the network layer, creates a global view of the energy in the network for optimizing its networkwide distribution. As a contribution, we define the interfacing APIs between these layers, delineate their responsibilities, identify corresponding challenges, and provide a first implementation of the energy stack. Our evaluation, using both experimental deployments and high-level simulations, establishes the feasibility of a layered solution to energy management under transient power.

Advances in micro-electronics and miniaturized mechanical systems are redefining the scope and extent of the energy constraints found in battery-operated wireless sensor networks (WSNs). On one hand, ambient energy harvesting may prolong the systems’ lifetime or possibly enable perpetual operation. On the other hand, wireless energy transfer allows systems to decouple the energy sources from the sensing locations, enabling deployments previously unfeasible. As a result of applying these technologies to WSNs, the assumption of a finite energy budget is replaced with that of potentially infinite , yet intermittent , energy supply, profoundly impacting the design, implementation, and operation of WSNs. This article discusses these aspects by surveying paradigmatic examples of existing solutions in both fields and by reporting on real-world experiences found in the literature. The discussion is instrumental in providing a foundation for selecting the most appropriate energy harvesting or wireless transfer technology based on the application at hand. We conclude by outlining research directions originating from the fundamental change of perspective that energy harvesting and wireless transfer bring about.

Infected machines pose threats to not only their users, but also their network owners (ISPs and enterprises). To neutralize the effect of these infected machines, common solutions span two ends of an architectural spectrum; either fully distributed solutions that are host-based, or completely centralized appliances at the network core. We present NetworkRadar, inspired by an SDN-enabled ISP framework, that operates in between these extremes and contains the benefits of both these approaches. We perform data-plane intensive event monitoring at aggregation points close to customers, and maintain a centralized control plane for correlating and high-granularity blocking of malicious bot activity. Here we present the architecture of our solution and evaluate a prototype deployment over an isolated slice of an ISP network, showing its viability due to a negligible (<;1%) impact on customer throughput and its control plane scaling linearly to the customer base.

Botnets are an evolutionary form of malware, unique in requiring network connectivity for herding by a botmaster that allows coordinated attacks as well as dynamic evasion from detection. Thus, the most interesting features of a bot relate to its rapidly evolving network behavior. The few academic and commercial malware observation systems that exist, however, are either proprietary or have large cost and management overhead. Moreover, the network behavior of bots changes considerably under different operational contexts. We first identify these various contexts that can impact its fingerprint. We then present Titan: a system that generates faithful network fingerprints by recreating all these contexts and stressing the bot with different network settings and host interactions. This effort includes a semi-automated and tunable containment policy to prevent bot proliferation. Most importantly, Titan has low cost overhead as a minimal setup requires just two machines, while the provision of a user-friendly web interface reduces the setup and management overhead. We then show a fingerprint of the Crypto locker bot to demonstrate automatic detection of its domain generation algorithm (DGA). We also demonstrate the effective identification of context specific behavior with a controlled deployment of Zeus botnet.

poster Share on POSTER: BotFlex: a community-driven tool for botnetdetection Authors: Sheharbano Khattak Independent Researcher, King's Lynn, United Kingdom Independent Researcher, King's Lynn, United KingdomView Profile , Zaafar Ahmed SysNet, National Univ. of Computer & Emerging Sciences., Islamabad, Pakistan SysNet, National Univ. of Computer & Emerging Sciences., Islamabad, PakistanView Profile , Affan Syed SysNet, National Univ. of Computer & Emerging Sciences., Islamabad, Pakistan SysNet, National Univ. of Computer & Emerging Sciences., Islamabad, PakistanView Profile , Syed Ali Khayam PLUMgrid, Inc., Sunnyvale, CA, USA PLUMgrid, Inc., Sunnyvale, CA, USAView Profile Authors Info & Claims CCS '13: Proceedings of the 2013 ACM SIGSAC conference on Computer & communications securityNovember 2013 Pages 1387–1390https://doi.org/10.1145/2508859.2512507Online:04 November 2013Publication History 4citation304DownloadsMetricsTotal Citations4Total Downloads304Last 12 Months5Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

Software-defined networking (SDN) is envisioned to provide a centralized interface to programmatically manage networking elements. However, despite its conceptual simplicity, current switch and SDN architectures have poor performance with little support to innovate and test novel SDN applications. We propose an application extensibility framework that allows researchers to build new SDN applications without requiring modification to the OpenFlow-based plumbing available today. We also employ both hardware and software packet processing capabilities of switching elements by offloading intensive per-packet processing onto the switch processing pipeline using dynamically loadable packet processing modules (PPMs). Our architecture thus allows flexibility in the type of applications alongside high switching performance. We believe that our architecture will unleash the potential of SDN by inspiring the SDN “killer app”. We evaluate our framework using an encryption middlebox application and show a two orders-of-magnitude improvement over an implementation using the current SDN architecture when using hardware offload blocks.

The principles of sensor networks—low-power, wireless, in-situ sensing with many inexpensive sensors—are only recently penetrating into underwater research. Acoustic communication is best suited for underwater communication, with much lower attenuation than RF, but acoustic propagation is five orders-of-magnitude slower than RF, so propagation times stretch to hundreds of milliseconds. Low-power wakeup tones are present in new underwater acoustic modems, and when added to applications and MAC protocols they reduce energy consumption wasted on idle listening. Unfortunately, underwater acoustic tones suffer from self-multipath —echoes unique to the latency that can completely defeat their protocol advantages. We introduce Self-Reflection Tone Learning (SRTL), a novel approach where nodes use Bayesian techniques to address interference by learning to discriminate self-reflections from noise and independent communication. We present detailed experiments using an acoustic modem in controlled and uncontrolled, in-air and underwater environments. These experiments demonstrate that SRTL's knowledge corresponds to physical-world predictions, that it can cope with underwater noise and reasonable levels of artificial noise, and that it can track a changing multipath environment. Simulations confirm that these real-world experiments generalize over a wide range of conditions.

Sensornets promise to extend automated monitoring and control into industrial processes. In spite of great progress made in sensornet design, installation and operational costs can impede their widespread adoption---current practices of infrequent, manual observation are often seen as sufficient and more cost effective than automation, even for key business processes. In this paper we present two new approaches to reduce these costs, and we apply those approaches to rapidly detect blockages in steam pipelines of a production oilfield. First, we eliminate the high cost of bringing power to the field by generating electricity from heat, exploiting the high temperature of the very pipelines we monitor. We demonstrate that for temperature differences of 80 °C or more, we are able to sustain sensornet operation without grid electricity or batteries. Second, we show that non-invasive sensing can reduce the cost of sensing by avoiding sensors that pierce the pipeline and have high installation cost with interruption to production. Our system instead uses surface temperature to infer full or partial blockages in steam pipelines and full blockages in hot water pipelines. Finally, we evaluate our "steam-powered sensing" system to monitor potential blockages in steam pipeline chokes at a production oilfield. We also show the generality of our algorithm by applying it to detect water pipeline blockages in our lab. To our knowledge, this paper describes the first field-tested deployment of an industrial sensornet that employs non-solar energy harvesting.

The principles of sensor networks, with inexpensive low-power, wireless, in-situ sensing, are today going underwater with acoustic communication. With large acoustic delays, new modems use techniques such as low-power wakeup tones to reduce energy otherwise wasted on idle listening, and recent applications and MAC protocols integrate tones in their operation. While all wireless data-networks suffer from receiver-multipath, we show that tone-echos cause self-multipath for tone-based protocols. We address this interference with Self-Reflection Tone Learning (SRTL), a novel approach which uses Bayesian techniques to discriminate echos from noise or communication from other nodes. We present experiments from controlled environments to show that SRTL's knowledge corresponds to physical-world predictions, and that it can tolerate random noise up to at least two false triggers per sample.

In many cases, sensornets require continuous monitoring, 24x7, at remote, inaccessible locations making energy management a critical part of most sensornets. The sensornet research community has explored energy conservation and energy harvesting to address this problem of long-lived sensornets. Energy conservation is a primary concern in almost all sensornet work, and techniques from low-power hardware and OSes to coordinated network protocols and applications. Complementing energy conservation, energy harvesting gathers new energy from the environment.

This paper introduces T-Lohi, a new class of distributed and energy-efficient media-access protocols (MAC) for underwater acoustic sensor networks (UWSN). MAC design for UWSN faces significant challenges. For example, acoustic communication suffers from latencies five orders-of-magnitude larger than radio communication, so a naive CSMA MAC would require very long listen time resulting in low throughput and poor energy efficiency. In this paper, we first identify unique characteristics in underwater networking that may affect all MACs, such as space-time uncertainty and deafness conditions. We then develop T-Lohi employing a novel tone-based contention resolution mechanism that exploits space-time uncertainty and high latency to detect collisions and count contenders, achieving good throughput across all offered loads. Lohi uses our low-power wake-up receiver to significantly reduce energy consumption. Finally, we evaluate design choices and protocol performance through extensive simulation. The results show that the energy cost of packet transmission is within 3-9 % of optimal, and that Lohi achieves good channel utilization, within 30% utilization of the theoretical maximum. We also show that Lohi is stable and fair under both low and very high offered loads.

No abstract available.

This paper introduces T-Lohi, a new class of distributed and energy-efficient media-access protocols (MAC) for underwater acoustic sensor networks (UWSN). MAC design for UWSN faces significant challenges. For example, acoustic communication suffers from latencies five orders-of-magnitude larger than radio communication, so a naive CSMA MAC would require very long listen time resulting in low throughput and poor energy efficiency. In this paper, we first identify unique characteristics in underwater networking that may affect all MACs, such as space-time uncertainty and deafness conditions. We then develop T-Lohi employing a novel tone-based contention resolution mechanism that exploits space-time uncertainty and high latency to detect collisions and count contenders, achieving good throughput across all offered loads. T-Lohi exploits a low-power wake-up receiver to significantly reduce energy consumption. We evaluate design choices and protocol performance through extensive simulation. Finally, we compare T-Lohi against a few canonical MAC protocols. The results show that the energy cost of packet transmission is within 3-9% of optimal, and that Lohi achieves good channel utilization, within 30% utilization of the theoretical maximum. We also show that Lohi is stable and fair under both low and very high offered loads. Finally, we compare Lohi with other alternatives, including TDMA, CSMA, and ALOHA. Except for TDMA under heavy load, Lohi provides the best utilization in all cases, and it is always the most energy efficient.

Abstract — Distributed time synchronization is an important part of a sensor network where sensing and actuation must be coordinated across multiple nodes. Several time synchronization protocol that maximize accuracy and energy conservation have been developed, including FTSP, TPSN, and RBS. All of these assume nearly instantaneous wireless communication between sensor nodes; each of them work well in today’s RF-based sensor networks. We are just beginning to explore underwater sensor networks where communication is primarily via acoustic telemetry. With acoustic communication, where the propagation speed is nearly five orders of magnitude slower than RF, assumptions about rapid communication are incorrect and new approaches to time synchronization are required. We present Time Synchronization for High Latency (TSHL), designed assuming such high latency propagation. We show through analysis and simulation that it achieves precise time synchronization with minimal energy cost. Although at very short distances existing protocols are adequate, TSHL shows twice the accuracy at 500m, demonstrating the need to model both clock skew and propagation latency. I.

This paper explores applications and challenges for underwater sensor networks. We highlight potential applications to off-shore oilfields for seismic monitoring, equipment monitoring, and underwater robotics. We identify research directions in short-range acoustic communications, MAC, time synchronization, and localization protocols for high-latency acoustic networks, long-duration network sleeping, and application-level data scheduling. We describe our preliminary design on short-range acoustic communication hardware, and summarize results of high-latency time synchronization