The Cache Inference Problem and its Application to Content and Request Routing

In many networked applications, independent caching agents cooperate by servicing each other's miss streams, without revealing the operational details of the caching mechanisms they employ. Inference of such details could be instrumental for many other processes. For example, it could be used for optimized forwarding (or routing) of one's own miss stream (or content) to available proxy caches, or for making cache-aware resource management decisions. In this paper, we introduce the Cache Inference Problem (CIP) as that of inferring the characteristics of a caching agent, given the miss stream of that agent. While CIP is insolvable in its most general form, there are special cases of practical importance in which it is, including when the request stream follows an Independent Reference Model (IRM) with generalized power-law (GPL) demand distribution. To that end, we design two basic "litmus" tests that are able to detect LFU and LRU replacement policies, the effective size of the cache and of the object universe, and the skewness of the GPL demand for objects. Using extensive experiments under synthetic as well as real traces, we show that our methods infer such characteristics accurately and quite efficiently, and that they remain robust even when the IRM/GPL assumptions do not hold, and even when the underlying replacement policies are not "pure" LFU or LRU. We exemplify the value of our inference framework by considering example applications.

A nested location-routing heuristic using route length estimation

A nested heuristic approach that uses route length approximation is proposed to solve the location-routing problem. A new estimation formula for route length approximation is also developed. The heuristic is evaluated empirically against the sequential method and a recently developed nested method for location routing problems. This testing is carried out on a set of problems of 400 customers and around 15 to 25 depots with good results.

The many-to-many location-routing problem

In this paper the many to many location routing problem is introduced, and its relationship to various problems in distribution management is emphasised. Useful mathematical formulations which can be easily extended to cater for other related problems are produced. Techniques for tackling this complex distribution problem are also outlined.

Multilevel refinement for the vehicle routing problem

Multilevel approaches to computational problems are pervasive across many areas of applied mathematics and scientific computing. The multilevel paradigm uses recursive coarsening to create a hierarchy of approximations to the original problem, then an initial solution is found for the coarsest problem and iteratively refined and improved at each level, coarsest to finest. The solution process is aided by the global perspective (or `global view') imparted to the optimisation by the coarsening. This paper looks at their application to the Vehicle Routing Problem.

Multilevel refinement strategies for the capacity vehicle routing problem

We discuss the application of the multilevel (ML) refinement technique to the Vehicle Routing Problem (VRP), and compare it to its single-level (SL) counterpart. Multilevel refinement recursively coarsens to create a hierarchy of approximations to the problem and refines at each level. A SL algorithm, which uses a combination of standard VRP heuristics, is developed first to solve instances of the VRP. A ML version, which extends the global view of these heuristics, is then created, using variants of the construction and improvement heuristics at each level. Finally some multilevel enhancements are developed. Experimentation is used to find suitable parameter settings and the final version is tested on two well-known VRP benchmark suites. Results comparing both SL and ML algorithms are presented.

The application of multilevel refinement to the vehicle routing problem

We discuss the application of the multilevel (ML) refinement technique to the Vehicle Routing Problem (VRP), and compare it to its single-level (SL) counterpart. Multilevel refinement recursively coarsens to create a hierarchy of approximations to the problem and refines at each level. A SL heuristic, termed the combined node-exchange composite heuristic (CNCH), is developed first to solve instances of the VRP. A ML version (the ML-CNCH) is then created, using the construction and improvement heuristics of the CNCH at each level. Experimentation is used to find a suitable combination, which extends the global view of these heuristics. Results comparing both SL and ML are presented.

The dependence of power consumption of pneumatic conveying systems upon bulk material properties, pipeline bore and routing, and mode of flow

In this paper the dependence of the power consumption of pneumatic conveyors upon conveyed materials, pipeline route and bore, and mode of flow has been examined. The findings are that, with different materials and modes of flow, not only is the amount of power consumed very different but it varies in different ways with pipe bore and routing. Additionally it has been found that, for any given conveying system, the choice of air mover also has a strong influence on the power requirement.

Equalisation of time variant multipath channels using amplitude banded LMS algorithms

For the purpose of equalisation of rapidly time variant multipath channels, we derive a novel adaptive algorithm, the amplitude banded LMS (ABLMS); which implements a nonlinear adaptation based on a coefficient matrix. Then we develop the: ABLMS algorithm as the adaptation procedure for a linear transversal equaliser (LTE) and a decision feedback equaliser (DFE) where a parallel adaptation scheme is deployed. Computer simulations demonstrate that with a small increase of computational complexity, the ABLMS based parallel equalisers provide a significant improvement related to the conventional LMS DFE and the LMS LTE in the case of a second order Markov communication channel model.

Bit error rate performance enhancement of a retrodirective array over a conventional fixed beam array in a dynamic multipath environment

In this paper, we provide experimental evidence to show that enhanced bit error rate (BER) performance is possible using a retrodirective array operating in a dynamically varying multipath environment. The operation of such a system will be compared to that obtained by a conventional nonretrodirective array. The ability of the array to recover amplitude shift keyed encoded data transmitted from a remote location whose position is not known a priori is described. In addition, its ability to retransmit data inserted at the retrodirective array back to a spatially remote beacon location whose position is also not known beforehand is also demonstrated. Comparison with an equivalent conventional fixed beam antenna array utilizing an identical radiating aperture arrangement to that of the retrodirective array are given. These show that the retrodirective array can effectively exploit the presence of time varying multipath in order to give significant reductions in BER over what can be otherwise achieved. Additionally, the retrodirective system is shown to be able to deliver low BER regardless of whether line of sight is present or absent.