Interference-Aware Scheduling Using Geometric Constraints

The large scale parallel and distributed platforms produce a continuously increasing amount of data which have to be stored, exchanged and used by various jobs allocated on different nodes of the platform. The management of this huge communication demand is crucial for the performance of the system. Meanwhile, we have to deal with more interferences as the trend is to use a single all-purpose interconnection network. In this paper, we consider two different types of communications: the flows induced by data exchanges during computations and the flows related to Input/Output operations. We propose a general model for interference-aware scheduling, where explicit communications are replaced by external topological constraints. Specifically, we limit the interferences of both communication types by adding geometric constraints on the allocation of jobs into machines. The proposed constraints reduce implicitly the data movements by restricting the set of possible allocations for each job. We present this methodology on the case study of simple network topologies, namely the line and the ring. We propose theoretical lower and upper bounds under different assumptions with respect to the platform and jobs characteristics. The obtained results illustrate well the difficulty of the problem even on simple topologies

Optimality of Treating Interference as Noise: A Combinatorial Perspective

For single-antenna Gaussian interference channels, we re-formulate the problem of determining the Generalized Degrees of Freedom (GDoF) region achievable by treating interference as Gaussian noise (TIN) derived in [3] from a combinatorial perspective. We show that the TIN power control problem can be cast into an assignment problem, such that the globally optimal power allocation variables can be obtained by well-known polynomial time algorithms. Furthermore, the expression of the TIN-Achievable GDoF region (TINA region) can be substantially simplified with the aid of maximum weighted matchings. We also provide conditions under which the TINA region is a convex polytope that relax those in [3]. For these new conditions, together with a channel connectivity (i.e., interference topology) condition, we show TIN optimality for a new class of interference networks that is not included, nor includes, the class found in [3]. Building on the above insights, we consider the problem of joint link scheduling and power control in wireless networks, which has been widely studied as a basic physical layer mechanism for device-to-device (D2D) communications. Inspired by the relaxed TIN channel strength condition as well as the assignment-based power allocation, we propose a low-complexity GDoF-based distributed link scheduling and power control mechanism (ITLinQ+) that improves upon the ITLinQ scheme proposed in [4] and further improves over the heuristic approach known as FlashLinQ. It is demonstrated by simulation that ITLinQ+ provides significant average network throughput gains over both ITLinQ and FlashLinQ, and yet still maintains the same level of implementation complexity. More notably, the energy efficiency of the newly proposed ITLinQ+ is substantially larger than that of ITLinQ and FlashLinQ, which is desirable for D2D networks formed by battery-powered devices.Comment: A short version has been presented at IEEE International Symposium on Information Theory (ISIT 2015), Hong Kon

Optimal placement of a limited number of observations for period searches

Robotic telescopes present the opportunity for the sparse temporal placement of observations when period searching. We address the best way to place a limited number of observations to cover the dynamic range of frequencies required by an observer. We show that an observation distribution geometrically spaced in time can minimise aliasing effects arising from sparse sampling, substantially improving signal detection quality. The base of the geometric series is however a critical factor in the overall success of this strategy. Further, we show that for such an optimal distribution observations may be reordered, as long as the distribution of spacings is preserved, with almost no loss of quality. This implies that optimal observing strategies can retain significant flexibility in the face of scheduling constraints, by providing scope for on-the-fly adaptation. Finally, we present optimal geometric samplings for a wide range of common observing scenarios, with an emphasis on practical application by the observer at the telescope. Such a sampling represents the best practical empirical solution to the undersampling problem that we are aware of. The technique has applications to robotic telescope and satellite observing strategies, where target acquisition overheads mean that a greater total target exposure time (and hence signal-to-noise) can often in practice be achieved by limiting the number of observations.Comment: 8 pages with 16 figure

On Energy Efficient Hierarchical Cross-Layer Design: Joint Power Control and Routing for Ad Hoc Networks

In this paper, a hierarchical cross-layer design approach is proposed to increase energy efficiency in ad hoc networks through joint adaptation of nodes' transmitting powers and route selection. The design maintains the advantages of the classic OSI model, while accounting for the cross-coupling between layers, through information sharing. The proposed joint power control and routing algorithm is shown to increase significantly the overall energy efficiency of the network, at the expense of a moderate increase in complexity. Performance enhancement of the joint design using multiuser detection is also investigated, and it is shown that the use of multiuser detection can increase the capacity of the ad hoc network significantly for a given level of energy consumption.Comment: To appear in the EURASIP Journal on Wireless Communications and Networking, Special Issue on Wireless Mobile Ad Hoc Network