Competitive analysis of static-priority partitioned scheduling on uniform multiprocessors

Consider the problem of scheduling a set of sporadically arriving tasks on a uniform multiprocessor with the goal of meeting deadlines. A processor p has the speed Sp. Tasks can be preempted but they cannot migrate between processors. On each processor, tasks are scheduled according to rate-monotonic. We propose an algorithm that can schedule all task sets that any other possible algorithm can schedule assuming that our algorithm is given processors that are √2 / √2−1 ≈ 3.41 times faster. No such guarantees are previously known for partitioned static-priority scheduling on uniform multiprocessors.

Exploiting a prioritized MAC protocol to efficiently compute interpolations

Consider a network where all nodes share a single broadcast domain such as a wired broadcast network. Nodes take sensor readings but individual sensor readings are not the most important pieces of data in the system. Instead, we are interested in aggregated quantities of the sensor readings such as minimum and maximum values, the number of nodes and the median among a set of sensor readings on different nodes. In this paper we show that a prioritized medium access control (MAC) protocol may advantageously be exploited to efficiently compute aggregated quantities of sensor readings. In this context, we propose a distributed algorithm that has a very low time and message-complexity for computing certain aggregated quantities. Importantly, we show that if every sensor node knows its geographical location, then sensor data can be interpolated with our novel distributed algorithm, and the message-complexity of the algorithm is independent of the number of nodes. Such an interpolation of sensor data can be used to compute any desired function; for example the temperature gradient in a room (e.g., industrial plant) densely populated with sensor nodes, or the gas concentration gradient within a pipeline or traffic tunnel.

A two-competitive approximate schedulability analysis of CAN

Consider the problem of deciding whether a set of n sporadic message streams meet deadlines on a Controller Area Network (CAN) bus for a specified priority assignment. It is assumed that message streams have implicit deadlines and no release jitter. An algorithm to solve this problem is well known but unfortunately it time complexity is non-polynomial. We present an algorithm with polynomial time-complexity for computing an upper bound on the response times. Clearly, if the upper bound on the response time does not exceed the deadline then all deadlines are met. The pessimism of our approach is proven: if the upper bound of the response time exceeds the deadline then the response time exceeds the deadline as well for a CAN network with half the speed.

Exact analysis of TDMA with slot skipping

Consider a communication medium shared among a set of computer nodes; these computer nodes issue messages that are requested to be transmitted and they must finish their transmission before their respective deadlines. TDMA/SS is a protocol that solves this problem; it is a specific type of Time Division Multiple Access (TDMA) where a computer node is allowed to skip its time slot and then this time slot can be used by another computer node. We present an algorithm that computes exact queuing times for TDMA/SS in conjunction with Rate-Monotonic (RM) or Earliest- Deadline-First (EDF).

Uniprocessor EDF scheduling with mode change

Consider the problem of scheduling sporadically-arriving tasks with implicit deadlines using Earliest-Deadline-First (EDF) on a single processor. The system may undergo changes in its operational modes and therefore the characteristics of the task set may change at run-time. We consider a well-established previously published mode-change protocol and we show that if every mode utilizes at most 50% of the processing capacity then all deadlines are met. We also show that there exists a task set that misses a deadline although the utilization exceeds 50% by just an arbitrarily small amount. Finally, we present, for a relevant special case, an exact schedulability test for EDF with mode change.

Sporadic multiprocessor scheduling with few preemptions

Consider the problem of scheduling n sporadic tasks so as to meet deadlines on m identical processors. A task is characterised by its minimum interarrival time and its worst-case execution time. Tasks are preemptible and may migrate between processors. We propose an algorithm with limited migration, configurable for a utilisation bound of 88% with few preemptions (and arbitrarily close to 100% with more preemptions).

Scheduling arbitrary-deadline sporadic task systems on multiprocessors

A new algorithm is proposed for scheduling preemptible arbitrary-deadline sporadic task systems upon multiprocessor platforms, with interprocessor migration permitted. This algorithm is based on a task-splitting approach - while most tasks are entirely assigned to specific processors, a few tasks (fewer than the number of processors) may be split across two processors. This algorithm can be used for two distinct purposes: for actually scheduling specific sporadic task systems, and for feasibility analysis. Simulation- based evaluation indicates that this algorithm offers a significant improvement on the ability to schedule arbitrary- deadline sporadic task systems as compared to the contemporary state-of-art. With regard to feasibility analysis, the new algorithm is proved to offer superior performance guarantees in comparison to prior feasibility tests.

How a cyber-physical system can efficiently obtain a snapshot of physical information even in the presence of sensor faults

We present a distributed algorithm for cyber-physical systems to obtain a snapshot of sensor data. The snapshot is an approximate representation of sensor data; it is an interpolation as a function of space coordinates. The new algorithm exploits a prioritized medium access control (MAC) protocol to efficiently transmit information of the sensor data. It scales to a very large number of sensors and it is able to operate in the presence of sensor faults.

The utilization bound of static-priority preemptive partitioned multiprocessor scheduling is 50%

This paper studies static-priority preemptive scheduling on a multiprocessor using partitioned scheduling. We propose a new scheduling algorithm and prove that if the proposed algorithm is used and if less than 50% of the capacity is requested then all deadlines are met. It is known that for every static-priority multiprocessor scheduling algorithm, there is a task set that misses a deadline although the requested capacity is arbitrary close to 50%.

Multiprocessor scheduling with few preemptions

Consider the problem of scheduling a set of periodically arriving tasks on a multiprocessor with the goal of meeting deadlines. Processors are identical and have the same speed. Tasks can be preempted and they can migrate between processors. We propose an algorithm with a utilization bound of 66% and with few preemptions. It can trade a higher utilization bound for more preemption and in doing so it has a utilization bound of 100%.

Implementation of a dominance protocol for wireless medium access

Consider the problem of scheduling sporadic message transmission requests with deadlines. For wired channels, this has been achieved successfully using the CAN bus. For wireless channels, researchers have recently proposed a similar solution; a collision-free medium access control (MAC) protocol that implements static-priority scheduling. Unfortunately no implementation has been reported, yet. We implement and evaluate it to find that the implementation indeed is collision-free and prioritized. This allows us to develop schedulability analysis for the implementation. We measure the response times of messages in our implementation and find that our new response-time analysis indeed offers an upper bound on the response times. This enables a new class of wireless real-time systems with timeliness guarantees for sporadic messages and it opens-up a new research area: schedulability analysis for wireless networks.

Task assignment algorithms for two-type heterogeneous multiprocessors

Consider the problem of assigning implicit-deadline sporadic tasks on a heterogeneous multiprocessor platform comprising two different types of processors—such a platform is referred to as two-type platform. We present two low degree polynomial time-complexity algorithms, SA and SA-P, each providing the following guarantee. For a given two-type platform and a task set, if there exists a task assignment such that tasks can be scheduled to meet deadlines by allowing them to migrate only between processors of the same type (intra-migrative), then (i) using SA, it is guaranteed to find such an assignment where the same restriction on task migration applies but given a platform in which processors are 1+α/2 times faster and (ii) SA-P succeeds in finding a task assignment where tasks are not allowed to migrate between processors (non-migrative) but given a platform in which processors are 1+α times faster. The parameter 0<α≤1 is a property of the task set; it is the maximum of all the task utilizations that are no greater than 1. We evaluate average-case performance of both the algorithms by generating task sets randomly and measuring how much faster processors the algorithms need (which is upper bounded by 1+α/2 for SA and 1+α for SA-P) in order to output a feasible task assignment (intra-migrative for SA and non-migrative for SA-P). In our evaluations, for the vast majority of task sets, these algorithms require significantly smaller processor speedup than indicated by their theoretical bounds. Finally, we consider a special case where no task utilization in the given task set can exceed one and for this case, we (re-)prove the performance guarantees of SA and SA-P. We show, for both of the algorithms, that changing the adversary from intra-migrative to a more powerful one, namely fully-migrative, in which tasks can migrate between processors of any type, does not deteriorate the performance guarantees. For this special case, we compare the average-case performance of SA-P and a state-of-the-art algorithm by generating task sets randomly. In our evaluations, SA-P outperforms the state-of-the-art by requiring much smaller processor speedup and by running orders of magnitude faster.

Real-time scheduling with resource sharing on heterogeneous multiprocessors

Consider the problem of scheduling a task set τ of implicit-deadline sporadic tasks to meet all deadlines on a t-type heterogeneous multiprocessor platform where tasks may access multiple shared resources. The multiprocessor platform has m k processors of type-k, where k∈{1,2,…,t}. The execution time of a task depends on the type of processor on which it executes. The set of shared resources is denoted by R. For each task τ i , there is a resource set R i ⊆R such that for each job of τ i , during one phase of its execution, the job requests to hold the resource set R i exclusively with the interpretation that (i) the job makes a single request to hold all the resources in the resource set R i and (ii) at all times, when a job of τ i holds R i , no other job holds any resource in R i . Each job of task τ i may request the resource set R i at most once during its execution. A job is allowed to migrate when it requests a resource set and when it releases the resource set but a job is not allowed to migrate at other times. Our goal is to design a scheduling algorithm for this problem and prove its performance. We propose an algorithm, LP-EE-vpr, which offers the guarantee that if an implicit-deadline sporadic task set is schedulable on a t-type heterogeneous multiprocessor platform by an optimal scheduling algorithm that allows a job to migrate only when it requests or releases a resource set, then our algorithm also meets the deadlines with the same restriction on job migration, if given processors 4×(1+MAXP×⌈|P|×MAXPmin{m1,m2,…,mt}⌉) times as fast. (Here MAXP and |P| are computed based on the resource sets that tasks request.) For the special case that each task requests at most one resource, the bound of LP-EE-vpr collapses to 4×(1+⌈|R|min{m1,m2,…,mt}⌉). To the best of our knowledge, LP-EE-vpr is the first algorithm with proven performance guarantee for real-time scheduling of sporadic tasks with resource sharing on t-type heterogeneous multiprocessors.

Politicization of non-political events

Spatial analysis and social network analysis typically take into consideration social processes in specific contexts of geographical or network space. The research in political science increasingly strives to model heterogeneity and spatial dependence. To better understand and geographically model the relationship between “non-political” events, streaming data from social networks, and political climate was the primary objective of the current study. Geographic information systems (GIS) are useful tools in the organization and analysis of streaming data from social networks. In this study, geographical and statistical analysis were combined in order to define the temporal and spatial nature of the data eminating from the popular social network Twitter during the 2014 FIFA World Cup. The study spans the entire globe because Twitter’s geotagging function, the fundamental data that makes this study possible, is not limited to a geographic area. By examining the public reactions to an inherenlty non-political event, this study serves to illuminate broader questions about social behavior and spatial dependence. From a practical perspective, the analyses demonstrate how the discussion of political topics fluсtuate according to football matches. Tableau and Rapidminer, in addition to a set basic statistical methods, were applied to find patterns in the social behavior in space and time in different geographic regions. It was found some insight into the relationship between an ostensibly non-political event – the World Cup - and public opinion transmitted by social media. The methodology could serve as a prototype for future studies and guide policy makers in governmental and non-governmental organizations in gauging the public opinion in certain geographic locations.

Analysis of panoramio photo tags in order to extract land use information

In the recent past, hardly anyone could predict this course of GIS development. GIS is moving from desktop to cloud. Web 2.0 enabled people to input data into web. These data are becoming increasingly geolocated. Big amounts of data formed something that is called "Big Data". Scientists still don't know how to deal with it completely. Different Data Mining tools are used for trying to extract some useful information from this Big Data. In our study, we also deal with one part of these data - User Generated Geographic Content (UGGC). The Panoramio initiative allows people to upload photos and describe them with tags. These photos are geolocated, which means that they have exact location on the Earth's surface according to a certain spatial reference system. By using Data Mining tools, we are trying to answer if it is possible to extract land use information from Panoramio photo tags. Also, we tried to answer to what extent this information could be accurate. At the end, we compared different Data Mining methods in order to distinguish which one has the most suited performances for this kind of data, which is text. Our answers are quite encouraging. With more than 70% of accuracy, we proved that extracting land use information is possible to some extent. Also, we found Memory Based Reasoning (MBR) method the most suitable method for this kind of data in all cases.