The spectrum sensing problem has gained new aspects with cognitive radio and opportunistic spectrum access concepts. It is one of the most challenging issues in cognitive radio systems. In this paper, a survey of spectrum sensing methodologies for cognitive radio is presented. Various aspects of spectrum sensing problem are studied from a cognitive radio perspective and multi-dimensional spectrum sensing concept is introduced. Challenges associated with spectrum sensing are given and enabling spectrum sensing methods are reviewed. The paper explains the cooperative sensing concept and its various forms. External sensing algorithms and other alternative sensing methods are discussed. Furthermore, statistical modeling of network traffic and utilization of these models for prediction of primary user behavior is studied. Finally, sensing features of some current wireless standards are given.

A survey of spectrum sensing algorithms for cognitive radio applications

http://cpham.perso.univ-pau.fr/ENSEIGNEMENT/PAU-UPPA/RESA-M2/Clustering-abasi.pdf

A survey on clustering algorithms for wireless sensor networks

Third-party cloud computing represents the promise of outsourcing as applied to computation. Services, such as Microsoft's Azure and Amazon's EC2, allow users to instantiate virtual machines (VMs) on demand and thus purchase precisely the capacity they require when they require it. In turn, the use of virtualization allows third-party cloud providers to maximize the utilization of their sunk capital costs by multiplexing many customer VMs across a shared physical infrastructure. However, in this paper, we show that this approach can also introduce new vulnerabilities. Using the Amazon EC2 service as a case study, we show that it is possible to map the internal cloud infrastructure, identify where a particular target VM is likely to reside, and then instantiate new VMs until one is placed co-resident with the target. We explore how such placement can then be used to mount cross-VM side-channel attacks to extract information from a target VM on the same machine.

/pdf/hey-you-get-off-of-my-cloud-exploring-information-leakage-in-4bex13z4ep.pdf

Hey, you, get off of my cloud: exploring information leakage in third-party compute clouds

Mobile-edge cloud computing is a new paradigm to provide cloud computing capabilities at the edge of pervasive radio access networks in close proximity to mobile users. In this paper, we first study the multi-user computation offloading problem for mobile-edge cloud computing in a multi-channel wireless interference environment. We show that it is NP-hard to compute a centralized optimal solution, and hence adopt a game theoretic approach for achieving efficient computation offloading in a distributed manner. We formulate the distributed computation offloading decision making problem among mobile device users as a multi-user computation offloading game. We analyze the structural property of the game and show that the game admits a Nash equilibrium and possesses the finite improvement property. We then design a distributed computation offloading algorithm that can achieve a Nash equilibrium, derive the upper bound of the convergence time, and quantify its efficiency ratio over the centralized optimal solutions in terms of two important performance metrics. We further extend our study to the scenario of multi-user computation offloading in the multi-channel wireless contention environment. Numerical results corroborate that the proposed algorithm can achieve superior computation offloading performance and scale well as the user size increases.

Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing

This paper discusses the design of a single channel full-duplex wireless transceiver. The design uses a combination of RF and baseband techniques to achieve full-duplexing with minimal effect on link reliability. Experiments on real nodes show the full-duplex prototype achieves median performance that is within 8% of an ideal full-duplexing system. This paper presents Antenna Cancellation, a novel technique for self-interference cancellation. In conjunction with existing RF interference cancellation and digital baseband interference cancellation, antenna cancellation achieves the amount of self-interference cancellation required for full-duplex operation. The paper also discusses potential MAC and network gains with full-duplexing. It suggests ways in which a full-duplex system can solve some important problems with existing wireless systems including hidden terminals, loss of throughput due to congestion, and large end-to-end delays.

/pdf/achieving-single-channel-full-duplex-wireless-communication-3pg630e002.pdf

Achieving single channel, full duplex wireless communication

DRAM memory is a major resource shared among cores in a chip multiprocessor (CMP) system. Memory requests from different threads can interfere with each other. Existing memory access scheduling techniques try to optimize the overall data throughput obtained from the DRAM and thus do not take into account inter-thread interference. Therefore, different threads running together on the same chip can ex- perience extremely different memory system performance: one thread can experience a severe slowdown or starvation while another is un- fairly prioritized by the memory scheduler. This paper proposes a new memory access scheduler, called the Stall-Time Fair Memory scheduler (STFM), that provides quality of service to different threads sharing the DRAM memory system. The goal of the proposed scheduler is to "equalize" the DRAM-related slowdown experienced by each thread due to interference from other threads, without hurting overall system performance. As such, STFM takes into account inherent memory characteristics of each thread and does not unfairly penalize threads that use the DRAM system without interfering with other threads. We show that STFM significantly reduces the unfairness in the DRAM system while also improving system throughput (i.e., weighted speedup of threads) on a wide variety of workloads and systems. For example, averaged over 32 different workloads running on an 8-core CMP, the ratio between the highest DRAM-related slowdown and the lowest DRAM-related slowdown reduces from 5.26X to 1.4X, while the average system throughput improves by 7.6%. We qualitatively and quantitatively compare STFM to one new and three previously- proposed memory access scheduling algorithms, including network fair queueing. Our results show that STFM provides the best fairness, system throughput, and scalability.

/pdf/stall-time-fair-memory-access-scheduling-for-chip-kj13rlydtp.pdf

Stall-Time Fair Memory Access Scheduling for Chip Multiprocessors

In a chip-multiprocessor (CMP) system, the DRAM system isshared among cores. In a shared DRAM system, requests from athread can not only delay requests from other threads by causingbank/bus/row-buffer conflicts but they can also destroy other threads’DRAM-bank-level parallelism. Requests whose latencies would otherwisehave been overlapped could effectively become serialized. As aresult both fairness and system throughput degrade, and some threadscan starve for long time periods.This paper proposes a fundamentally new approach to designinga shared DRAM controller that provides quality of service to threads,while also improving system throughput. Our parallelism-aware batchscheduler (PAR-BS) design is based on two key ideas. First, PARBSprocesses DRAM requests in batches to provide fairness and toavoid starvation of requests. Second, to optimize system throughput,PAR-BS employs a parallelism-aware DRAM scheduling policythat aims to process requests from a thread in parallel in the DRAMbanks, thereby reducing the memory-related stall-time experienced bythe thread. PAR-BS seamlessly incorporates support for system-levelthread priorities and can provide different service levels, includingpurely opportunistic service, to threads with different priorities.We evaluate the design trade-offs involved in PAR-BS and compareit to four previously proposed DRAM scheduler designs on 4-, 8-, and16-core systems. Our evaluations show that, averaged over 100 4-coreworkloads, PAR-BS improves fairness by 1.11X and system throughputby 8.3% compared to the best previous scheduling technique, Stall-Time Fair Memory (STFM) scheduling. Based on simple request prioritizationrules, PAR-BS is also simpler to implement than STFM.

http://users.ece.cmu.edu/~omutlu/pub/parbs_isca08.pdf

Parallelism-Aware Batch Scheduling: Enhancing both Performance and Fairness of Shared DRAM Systems

Networking over UHF white spaces is fundamentally different from conventional Wi-Fi along three axes: spatial variation, temporal variation, and fragmentation of the UHF spectrum. Each of these differences gives rise to new challenges for implementing a wireless network in this band. We present the design and implementation of Net7, the first Wi-Fi like system constructed on top of UHF white spaces. Net7 incorporates a new adaptive spectrum assignment algorithm to handle spectrum variation and fragmentation, and proposes a low overhead protocol to handle temporal variation. builds on a simple technique, called SIFT, that reduces the time to detect transmissions in variable channel width systems by analyzing raw signals in the time domain. We provide an extensive evaluation of the system in terms of a prototype implementation and detailed experimental and simulation results.

/pdf/white-space-networking-with-wi-fi-like-connectivity-10vrdfonkw.pdf

White space networking with wi-fi like connectivity

Energy has become a first-class design constraint in computer systems. Memory is a significant contributor to total system power. This paper introduces Flikker, an application-level technique to reduce refresh power in DRAM memories. Flikker enables developers to specify critical and non-critical data in programs and the runtime system allocates this data in separate parts of memory. The portion of memory containing critical data is refreshed at the regular refresh-rate, while the portion containing non-critical data is refreshed at substantially lower rates. This partitioning saves energy at the cost of a modest increase in data corruption in the non-critical data. Flikker thus exposes and leverages an interesting trade-off between energy consumption and hardware correctness. We show that many applications are naturally tolerant to errors in the non-critical data, and in the vast majority of cases, the errors have little or no impact on the application's final outcome. We also find that Flikker can save between 20-25% of the power consumed by the memory sub-system in a mobile device, with negligible impact on application performance. Flikker is implemented almost entirely in software, and requires only modest changes to the hardware.

/pdf/flikker-saving-dram-refresh-power-through-critical-data-4dx3bdq174.pdf

Flikker: saving DRAM refresh-power through critical data partitioning

Buffers in on-chip networks consume significant energy, occupy chip area, and increase design complexity. In this paper, we make a case for a new approach to designing on-chip interconnection networks that eliminates the need for buffers for routing or flow control. We describe new algorithms for routing without using buffers in router input/output ports. We analyze the advantages and disadvantages of bufferless routing and discuss how router latency can be reduced by taking advantage of the fact that input/output buffers do not exist. Our evaluations show that routing without buffers significantly reduces the energy consumption of the on-chip cache/processor-to-cache network, while providing similar performance to that of existing buffered routing algorithms at low network utilization (i.e., on most real applications). We conclude that bufferless routing can be an attractive and energy-efficient design option for on-chip cache/processor-to-cache networks where network utilization is low.

/pdf/a-case-for-bufferless-routing-in-on-chip-networks-2e289wpkbm.pdf

Thomas Moscibroda

Papers

Stall-Time Fair Memory Access Scheduling for Chip Multiprocessors

Parallelism-Aware Batch Scheduling: Enhancing both Performance and Fairness of Shared DRAM Systems

White space networking with wi-fi like connectivity

Flikker: saving DRAM refresh-power through critical data partitioning

A case for bufferless routing in on-chip networks