2,461 research outputs found
Business Model of a Botnet
Botnets continue to be an active threat against firms or companies and
individuals worldwide. Previous research regarding botnets has unveiled
information on how the system and their stakeholders operate, but an insight on
the economic structure that supports these stakeholders is lacking. The
objective of this research is to analyse the business model and determine the
revenue stream of a botnet owner. We also study the botnet life-cycle and
determine the costs associated with it on the basis of four case studies. We
conclude that building a full scale cyber army from scratch is very expensive
where as acquiring a previously developed botnet requires a little cost. We
find that initial setup and monthly costs were minimal compared to total
revenue.Comment: Proceedings of 2018, 26th Euromicro International conference on
Parallel, Distributed, and Network-Based Processing (PDP
Bandit-based Variable Fixing for Binary Optimization on GPU Parallel Computing
31st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 01-03 March 2023, Naples, Italy.This paper explores whether reinforcement learning is capable of enhancing metaheuristics for the quadratic unconstrained binary optimization (QUBO), which have recently attracted attention as a solver for a wide range of combinatorial optimization problems. In particular, we introduce a novel approach called the bandit-based variable fixing (BVF). The key idea behind BVF is to regard an execution of an arbitrary metaheuristic with a variable fixed as a play of a slot machine. Thus, BVF explores variables to fix with the maximum expected reward, and executes a metaheuristic at the same time. The bandit-based approach is then extended to fix multiple variables. To accelerate solving multi-armed bandit problem, we implement a parallel algorithm for BVF on a GPU. Our results suggest that our proposed BVF enhances original metaheuristics
Algon: a framework for supporting comparison of distributed algorithm performance
Programmers often need to use distributed algorithms to add non-functional behaviour such as mutual exclusion, deadlock detection and termination, to a distributed application. They find the selection and implementation of these algorithms daunting. Consequently, they have no idea which algorithm will be best for their particular application. To address this difficulty the Algon framework provides a set of pre-coded distributed algorithms for programmers to choose from, and provides a special performance display tool to support choice between algorithms. The performance tool is discussed. The developer of a distributed application will be able to observe the performance of each of the available algorithms according to a set of of widely accepted and easily-understandable performance metrics and compare and contrast the behaviour of the algorithms to support an informed choice. The strength of the Algon framework is that it does not require a working knowledge of algorithmic theory or functionality in order for the developer to use the algorithms
Shrink or Substitute: Handling Process Failures in HPC Systems using In-situ Recovery
Efficient utilization of today's high-performance computing (HPC) systems
with complex hardware and software components requires that the HPC
applications are designed to tolerate process failures at runtime. With low
mean time to failure (MTTF) of current and future HPC systems, long running
simulations on these systems require capabilities for gracefully handling
process failures by the applications themselves. In this paper, we explore the
use of fault tolerance extensions to Message Passing Interface (MPI) called
user-level failure mitigation (ULFM) for handling process failures without the
need to discard the progress made by the application. We explore two
alternative recovery strategies, which use ULFM along with application-driven
in-memory checkpointing. In the first case, the application is recovered with
only the surviving processes, and in the second case, spares are used to
replace the failed processes, such that the original configuration of the
application is restored. Our experimental results demonstrate that graceful
degradation is a viable alternative for recovery in environments where spares
may not be available.Comment: 26th Euromicro International Conference on Parallel, Distributed and
network-based Processing (PDP 2018
Generalized Extraction of Real-Time Parameters for Homogeneous Synchronous Dataflow Graphs
23rd Euromicro International Conference on Parallel, Distributed, and Network-Based Processing (PDP 2015). 4 to 6, Mar, 2015. Turku, Finland.Many embedded multi-core systems incorporate both dataflow applications with timing constraints and traditional
real-time applications. Applying real-time scheduling techniques on such systems provides real-time guarantees
that all running applications will execute safely without violating their deadlines. However, to apply traditional realtime
scheduling techniques on such mixed systems, a unified model to represent both types of applications
running on the system is required. Several earlier works have addressed this problem and solutions have been
proposed that address acyclic graphs, implicit-deadline models or are able to extract timing parameters
considering specific scheduling algorithms. In this paper, we present an algorithm for extracting real-time
parameters (offsets, deadlines and periods) that are independent of the schedulability analysis, other applications
running in the system, and the specific platform. The proposed algorithm: 1) enables applying traditional real-time
schedulers and analysis techniques on cyclic or acyclic Homogeneous Synchronous Dataflow (HSDF) applications
with periodic sources, 2) captures overlapping iterations, which is a main characteristic of the execution of
dataflow applications, 3) provides a method to assign offsets and individual deadlines for HSDF actors, and 4) is
compatible with widely used deadline assignment techniques, such as NORM and PURE. The paper proves the
correctness of the proposed algorithm through formal proofs and examples
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