Thomas Moscibroda

White space networking with wi-fi like connectivity

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.

The Complexity of Connectivity in Wireless Networks

We define and study the scheduling complexity in wireless networks, which expresses the theoretically achievable efficiency of MAC layer protocols. Given a set of communication requests in arbitrary networks, the scheduling complexity describes the amount of time required to successfully schedule all requests. The most basic and important network structure in wireless networks being connectivity, we study the scheduling complexity of connectivity, i.e., the minimal amount of time required until a connected structure can be scheduled. In this paper, we prove that the scheduling complexity of connectivity grows only polylogarithmically in the number of nodes. Specifically, we present a novel scheduling algorithm that successfully schedules a strongly connected set of links in time O(logn) even in arbitrary worst-case networks. On the other hand, we prove that standard MAC layer or scheduling protocols can perform much worse. Particularly, any protocol that either employs uniform or linear (a node’s transmit power is proportional to the minimum power required to reach its intended receiver) power assignment has a Ω(n) scheduling complexity in the worst case, even for simple communication requests. In contrast, our polylogarithmic scheduling algorithm allows many concurrent transmission by using an explicitly formulated non-linear power assignment scheme. Our results show that even in large-scale worst-case networks, there is no theoretical scalability problem when it comes to scheduling transmission requests, thus giving an interesting complement to the more pessimistic bounds for the capacity in wireless networks. All results are based on the physical model of communication, which takes into account that the signal-tonoise plus interference ratio (SINR) at a receiver must be above a certain threshold if the transmission is to be received correctly.

A case for bufferless routing in on-chip networks

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.

Allocating dynamic time-spectrum blocks in cognitive radio networks

A number of studies have shown the abundance of unused spectrum in the TV bands. This is in stark contrast to the overcrowding of wireless devices in the ISM bands. A recent trend to alleviate this disparity is the design of Cognitive Radios, which constantly sense the spectrum and opportunistically utilize unused frequencies in the TV bands. In this paper, we introduce the concept of a time-spectrum block to model spectrum reservation, and use it to present a theoretical formalization of the spectrum allocation problem in cognitive radio networks. We present a centralized and a distributed protocol for spectrum allocation and show that these protocols are close to optimal in most scenarios. We have implemented the distributed protocol in QualNet and show that our analysis closely matches the simulation results.

A case for adapting channel width in wireless networks

We study a fundamental yet under-explored facet in wireless communication -- the width of the spectrum over which transmitters spread their signals, or the channel width. Through detailed measurements in controlled and live environments, and using only commodity 802.11 hardware, we first quantify the impact of channel width on throughput, range, and power consumption. Taken together, our findings make a strong case for wireless systems that adapt channel width. Such adaptation brings unique benefits. For instance, when the throughput required is low, moving to a narrower channel increases range and reduces power consumption; in fixed-width systems, these two quantities are always in conflict. We then present a channel width adaptation algorithm, called SampleWidth, for the base case of two communicating nodes. This algorithm is based on a simple search process that builds on top of existing techniques for adapting modulation. Per specified policy, it can maximize throughput or minimize power consumption. Evaluation using a prototype implementation shows that SampleWidth correctly identities the optimal width under a range of scenarios. In our experiments with mobility, it increases throughput by more than 60% compared to the best fixed-width configuration.

Flikker: saving DRAM refresh-power through critical data partitioning

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 applications 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.

Topology control meets SINR: the scheduling complexity of arbitrary topologies

To date, topology control in wireless ad hoc and sensor networks--the study of how to compute from the given communication network a subgraph with certain beneficial properties .has been considered as a static problem only; the time required to actually schedule the links of a computed topology without message collision was generally ignored. In this paper we analyze topology control in the context of the physical Signal-to-Interference-plus-Noise-Ratio (SINR) model, focusing on the question of how and how fast the links of a resulting topology can actually be realized over time.For this purpose, we define and study a generalized version of the SINR model and obtain theoretical upper bounds on the scheduling complexity of arbitrary topologies in wireless networks. Specifically, we prove that even in worst-case networks, if the signals are transmitted with correctly assigned transmission power levels, the number of time slots required to successfully schedule all links of an arbitrary topology is proportional to the squared logarithm of the number of network nodes times a previously defined static interference measure Interestingly, although originally considered without explicit accounting for signal collision in the SINR model, this static interference measure plays an important role in the analysis of link scheduling with physical link interference. Our result thus bridges the gap between static graph-based interference models and the physical SINR model. Based on these results, we also show that when it comes to scheduling, requiring the communication links to be symmetric may imply significantly higher costs as opposed to topologies allowing unidirectional links.

SenseLess: A database-driven white spaces network

The most recent FCC ruling proposes relying on a database of incumbents as the primary means of determining white space availability at any white spaces device (WSD). While the ruling provides broad guidelines for the database, the specifics of its design, features, implementation, and use are yet to be determined. Furthermore, architecting a network where all WSDs rely on the database raises several systems and networking challenges that have remained unexplored. Also, the ruling treats the database only as a storehouse for incumbents. We believe that the mandated use of the database has an additional opportunity: a means to dynamically manage the RF spectrum. Motivated by this opportunity, in this paper we present SenseLess, a database driven white spaces network. As suggested by its very name, in SenseLess, WSDs obviate the need to sense the spectrum by relying entirely on a database service to determine white spaces availability. The service, using a combination of an up-to-date database of incumbents, sophisticated signal propagation modeling, and an efficient content dissemination mechanism ensures efficient, scalable, and safe white space network operation. We build, deploy, and evaluate SenseLess and compare our results to ground truth spectrum measurements. We present the unique system design considerations that arise due to operating over the white spaces. We also evaluate its efficiency and scalability. To the best of our knowledge, this is the first paper that identifies and examines the systems and networking challenges that arise from operating a white space network, which is solely dependent on a channel occupancy database.

The price of being near-sighted

Achieving a global goal based on local information is challenging, especially in complex and large-scale networks such as the Internet or even the human brain. In this paper, we provide an almost tight classification of the possible trade-off between the amount of local information and the quality of the global solution for general covering and packing problems. Specifically, we give a distributed algorithm using only small messages which obtains an (ρΔ)1/k-approximation for general covering and packing problems in time O(k2), where ρ depends on the LPs coefficients. If message size is unbounded, we present a second algorithm that achieves an O(n1/k) approximation in O(k) rounds. Finally, we prove that these algorithms are close to optimal by giving a lower bound on the approximability of packing problems given that each node has to base its decision on information from its k-neighborhood.

Dynamically replicated memory: building reliable systems from nanoscale resistive memories

DRAM is facing severe scalability challenges in sub-45nm tech- nology nodes due to precise charge placement and sensing hur- dles in deep-submicron geometries. Resistive memories, such as phase-change memory (PCM), already scale well beyond DRAM and are a promising DRAM replacement. Unfortunately, PCM is write-limited, and current approaches to managing writes must de- commission pages of PCM when the first bit fails. This paper presents dynamically replicated memory (DRM), the first hardware and operating system interface designed for PCM that allows continued operation through graceful degradation when hard faults occur. DRM reuses memory pages that con- tain hard faults by dynamically forming pairs of complementary pages that act as a single page of storage. No changes are required to the processor cores, the cache hierarchy, or the operating sys- tems page tables. By changing the memory controller, the TLBs, and the operating system to be DRM-aware, we can improve the lifetime of PCM by up to 40x over conventional error-detection techniques.