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This paper introduces the first objective space algorithm which can exactly find all supported and non-supported non-dominated solutions to a mixed-integer multi-objective linear program with an arbitrary number of objective functions. This…
The paper considers the problem of scheduling software modules on a multi-core processor, taking into account the limited bandwidth of the data bus and the precedence constraints. Two problem formulations with different levels of…
The prevailing assumption holds that on-orbit servicing (OOS) of mega-constellations is infeasible due to prohibitive fuel consumption incurred by multiple rendezvous maneuvers across vast and dispersed satellite populations. To address…
Real-time control systems often require dedicated hardware and software, including real-time operating systems, while many systems are available for off-line computing, mainly based on standard system units (PCs), standard network…
Centralized radio access network architectures consolidate the baseband operation towards a cloud-based platform, thereby allowing for efficient utilization of computing assets, effective inter-cell coordination, and exploitation of global…
The Mobile Edge Computing (MEC) system located close to the client allows mobile smart devices to offload their computations onto edge servers, enabling them to benefit from low-latency computing services. Both cloud service providers and…
It is becoming increasingly clear that, if a useful device for quantum computation will ever be built, it will be embodied by a classical computing machine with control over a truly quantum subsystem, this apparatus performing a mixture of…
Ecological sciences are using imagery from a variety of sources to monitor and survey populations and ecosystems. Very High Resolution (VHR) satellite imagery provide an effective dataset for large scale surveys. Convolutional Neural…
Mission-critical system, such as satellite systems, healthcare systems, and nuclear power plant control systems, undergo rigorous testing to ensure they meet specific operational requirements throughout their operation. This includes…
This paper describes the technology of data warehouse in healthcare decision-making and tools for support of these technologies, which is used to cancer diseases. The healthcare executive managers and doctors needs information about and…
Many algorithms for congestion control, scheduling, network measurement, active queue management, security, and load balancing require custom processing of packets as they traverse the data plane of a network switch. To run at line rate,…
With the significant advancements in optical computing platforms recently capable of performing various primitive operations, a seamless integration of optical computing into very fabric of optical communication links is envisioned, paving…
A system, which implements persistent objects, has to provide different opportunities to change the objects in arbitrary ways during their existence. A traditional realization of OO paradigm in modern programming systems has fundamental…
In a technological landscape that is quickly moving toward dense multi-CPU and multi-core computer systems, where using multithreading is an increasingly popular application design decision, it is important to choose a proper model for…
Today, we have required to accommodate a large number of users under a single base station. This can be possible only if we have some flexibility over the spectrum. Previously we have lots of multiplexing methods to accommodate large number…
With the advent of hundreds of cores on a chip to accelerate applications, the operating system (OS) needs to exploit the existing parallelism provided by the underlying hardware resources to determine the right amount of processes to be…
This article describes a geometric partitioning software that can be used for quick computation of data partitions on many-core HPC machines. It is most suited for dynamic applications with load distributions that vary with time.…
Based on the two observations that diverse applications perform better on different multicore architectures, and that different phases of an application may have vastly different resource requirements, Pal et al. proposed a novel…
Distributed learning is widely used for training large models on large datasets by distributing parts of the model or dataset across multiple devices and aggregating the computed results for subsequent computations or parameter updates.…
In this paper, we introduce a software-defined framework that enables the parallel utilization of all the programmable processing resources available in heterogeneous system-on-chip (SoC) including FPGA-based hardware accelerators and…