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List accessing problem has been studied as a problem of significant theoretical and practical interest in the context of linear search. Various list accessing algorithms have been proposed in the literature and their performances have been…
For the List Accessing Problem, Move-To-Front(MTF) algorithm has been proved to be the best performing online list accessing algorithm till date in the literature[10]. In this paper, we have made a comprehensive analysis of MTF algorithm…
List Accessing Problem is a well studied research problem in the context of linear search. Input to the list accessing problem is an unsorted linear list of distinct elements along with a sequence of requests, where each request is an…
The design and analysis of efficient algorithms with the knowledge of current and past inputs is a non-trivial and challenging research area in computer science. In many practical applications the future inputs are not available to the…
Data Prefetching is a technique that can hide memory latency by fetching data before it is needed by a program. Prefetching relies on accurate memory access prediction, to which task machine learning based methods are increasingly applied.…
In a previous paper by the second author,two Markov chain Monte Carlo perfect sampling algorithms -- one called coupling from the past (CFTP) and the other (FMMR) based on rejection sampling -- are compared using as a case study the…
This paper considers a natural generalization of the online list access problem in the paid exchange model, where additionally there can be precedence constraints ("dependencies") among the nodes in the list. For example, this…
A linear list is a collection of items that can be accessed sequentially. The cost of a request is the number of items that need to be examined before the desired item is located, i.e., the distance of the requested item from the beginning…
Routing algorithms for public transport, particularly the widely used RAPTOR and its variants, often face performance bottlenecks during the transfer relaxation phase, especially on dense transfer graphs, when supporting unlimited…
Fully-partitioned fixed-priority scheduling (FP-FPS) multiprocessor systems are widely found in real-time applications, where spin-based protocols are often deployed to manage the mutually exclusive access of shared resources.…
We study a multimodal journey planning scenario consisting of a public transit network and a transfer graph which represents a secondary transportation mode (e.g., walking, cycling, e-scooter). The objective is to compute Pareto-optimal…
An ad hoc network is an infrastructureless network in which nodes perform terminal as well as routing functions. A routing protocol is the only substitute to complete the communications in the absence of an access point. In spite of that…
Standard algorithms for reachability analysis of timed automata are sensitive to the order in which the transitions of the automata are taken. To tackle this problem, we propose a ranking system and a waiting strategy. This paper discusses…
Predicting multimodal future behavior of traffic participants is essential for robotic vehicles to make safe decisions. Existing works explore to directly predict future trajectories based on latent features or utilize dense goal candidates…
We study the journey planning problem for multimodal networks consisting of public transit and a non-schedule-based transfer mode (e.g., walking, bicycle, e-scooter). So far, all efficient algorithms for this problem either restrict usage…
We present T-REX (Transfer-Ranked EXploration), a new algorithm for journey planning in public transit networks on the country and continental scale. Our algorithm applies the principles of multi-level overlays to Trip-Based Public Transit…
Under dynamic traffic, service function chain (SFC) migration is considered as an effective way to improve resource utilization. However, the lack of future network information leads to non-optimal solutions, which motivates us to study…
We study web and mobile applications that are used to schedule advance service, from medical appointments to restaurant reservations. We model them as online weighted bipartite matching problems with non-stationary arrivals. We propose new…
Most recent successes on forecasting the people motion are based on LSTM models and all most recent progress has been achieved by modelling the social interaction among people and the people interaction with the scene. We question the use…
Time-Sensitive Networking (TSN) enables the transmission of multiple traffic types within a single network. While the performance of high-priority traffic has been extensively studied in recent years, the performance of low-priority traffic…