5,570 research outputs found
An Analytical Solution for Probabilistic Guarantees of Reservation Based Soft Real-Time Systems
We show a methodology for the computation of the probability of deadline miss
for a periodic real-time task scheduled by a resource reservation algorithm. We
propose a modelling technique for the system that reduces the computation of
such a probability to that of the steady state probability of an infinite state
Discrete Time Markov Chain with a periodic structure. This structure is
exploited to develop an efficient numeric solution where different
accuracy/computation time trade-offs can be obtained by operating on the
granularity of the model. More importantly we offer a closed form conservative
bound for the probability of a deadline miss. Our experiments reveal that the
bound remains reasonably close to the experimental probability in one real-time
application of practical interest. When this bound is used for the optimisation
of the overall Quality of Service for a set of tasks sharing the CPU, it
produces a good sub-optimal solution in a small amount of time.Comment: IEEE Transactions on Parallel and Distributed Systems, Volume:27,
Issue: 3, March 201
Efficient Machine-type Communication using Multi-metric Context-awareness for Cars used as Mobile Sensors in Upcoming 5G Networks
Upcoming 5G-based communication networks will be confronted with huge
increases in the amount of transmitted sensor data related to massive
deployments of static and mobile Internet of Things (IoT) systems. Cars acting
as mobile sensors will become important data sources for cloud-based
applications like predictive maintenance and dynamic traffic forecast. Due to
the limitation of available communication resources, it is expected that the
grows in Machine-Type Communication (MTC) will cause severe interference with
Human-to-human (H2H) communication. Consequently, more efficient transmission
methods are highly required. In this paper, we present a probabilistic scheme
for efficient transmission of vehicular sensor data which leverages favorable
channel conditions and avoids transmissions when they are expected to be highly
resource-consuming. Multiple variants of the proposed scheme are evaluated in
comprehensive realworld experiments. Through machine learning based combination
of multiple context metrics, the proposed scheme is able to achieve up to 164%
higher average data rate values for sensor applications with soft deadline
requirements compared to regular periodic transmission.Comment: Best Student Paper Awar
Real-time characteristics of switched ethernet for "1553B" -embedded applications : simulation and analysis
In our previous work , Full Duplex Switched Ethernet was put forward as an attractive candidate to replace the MIL-STD 1553B data bus, in next generation "1553B"-embedded applications. An analytic study was conducted, using the Network Calculus formalism, to evaluate the deterministic guarantees offered by our proposal. Obtained results showed the effectiveness of traffic shaping techniques, combined with priority handling mechanisms on Full Duplex Switched Ethernet in order to satisfy 1553B-like real-time constraints. In this paper, we extend this work by the use of simulation. This gives the possibility to capture additional characteristics of the proposed architecture with respect to the analytical study, which was basically used to evaluate worst cases and deterministic guarantees. Hence, to assess the real-time characteristics of our proposed interconnection technology, the results yielded by simulation are discussed and average latencies distributions are considered
Simplifying Wireless Social Caching
Social groups give the opportunity for a new form of caching. In this paper,
we investigate how a social group of users can jointly optimize bandwidth
usage, by each caching parts of the data demand, and then opportunistically
share these parts among themselves upon meeting. We formulate this problem as a
Linear Program (LP) with exponential complexity. Based on the optimal solution,
we propose a simple heuristic inspired by the bipartite set-cover problem that
operates in polynomial time. Furthermore, we prove a worst case gap between the
heuristic and the LP solutions. Finally, we assess the performance of our
algorithm using real-world mobility traces from the MIT Reality Mining project
dataset and two mobility traces that were synthesized using the SWIM model. Our
heuristic performs closely to the optimal in most cases, showing a better
performance with respect to alternative solutions.Comment: Parts of this work were accepted for publication in ISIT 2016. A
complete version is submitted to Transactions on Mobile Computin
Heuristic search under a deadline
In many heuristic search problems of practical interest, insufficient time is available to find a provably optimal solution. The currently accepted methods of finding a best possible sub-optimal solution within a time deadline are the anytime methods which do not directly consider the time remaining in the search. My thesis is that a deadline-cognizant approach, one which attempts to expend all available search effort towards a single final solution, has the potential for outperforming these methods.
To support this thesis I introduce two new deadline-cognizant algorithms: Deadline Aware Search and Deadline Decision Theoretic Search. These approaches use on-line measurements of search behavior to guide the search towards the best possible solution reachable before the deadline. An empirical analysis illustrates that DAS is capable of outperforming the current incumbent methods across a wide variety of domains, the first deadline-cognizant heuristic search algorithm to do so
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