Algorithms for Hierarchical and Semi-Partitioned Parallel Scheduling

We propose a model for scheduling jobs in a parallel machine setting that takes into account the cost of migrations by assuming that the processing time of a job may depend on the specific set of machines among which the job is migrated. For the makespan minimization objective, the model generalizes classical scheduling problems such as unrelated parallel machine scheduling, as well as novel ones such as semi-partitioned and clustered scheduling. In the case of a hierarchical family of machines, we derive a compact integer linear programming formulation of the problem and leverage its fractional relaxation to obtain a polynomial-time 2-approximation algorithm. Extensions that incorporate memory capacity constraints are also discussed

Feasibility Analysis of Conditional DAG Tasks

Feasibility analysis for Conditional DAG tasks (C-DAGs) upon multiprocessor platforms is shown to be complete for the complexity class pspace. It is shown that as a consequence integer linear programming solvers (ILP solvers) are likely to prove inadequate for such analysis. A demarcation is identified between the feasibility-analysis problems on C-DAGs that are efficiently solvable using ILP solvers and those that are not, by characterizing a restricted class of C-DAGs for which feasibility analysis is shown to be efficiently solvable using ILP solvers

Feasibility Tests for Recurrent Real-Time Tasks in the Sporadic DAG Model

A model has been proposed in [Baruah et al., in Proceedings of the IEEE Real-Time Systems Symposium 2012] for representing recurrent precedence-constrained tasks to be executed on multiprocessor platforms, where each recurrent task is modeled by a directed acyclic graph (DAG), a period, and a relative deadline. Each vertex of the DAG represents a sequential job, while the edges of the DAG represent precedence constraints between these jobs. All the jobs of the DAG are released simultaneously and have to be completed within some specified relative deadline. The task may release jobs in this manner an unbounded number of times, with successive releases occurring at least the specified period apart. The feasibility problem is to determine whether such a recurrent task can be scheduled to always meet all deadlines on a specified number of dedicated processors. The case of a single task has been considered in [Baruah et al., 2012]. The main contribution of this paper is to consider the case of multiple tasks. We show that EDF has a speedup bound of 2-1/m, where m is the number of processors. Moreover, we present polynomial and pseudopolynomial schedulability tests, of differing effectiveness, for determining whether a set of sporadic DAG tasks can be scheduled by EDF to meet all deadlines on a specified number of processors

ILP-based approaches to partitioning recurrent workloads upon heterogeneous multiprocessors

The problem of partitioning systems of independent constrained-deadline sporadic tasks upon heterogeneous multiprocessor platforms is considered. Several different integer linear program (ILP) formulations of this problem, offering different tradeoffs between effectiveness (as quantified by speedup bound) and running time efficiency, are presented

Comparison of methods for logic-query implementation

AbstractA logic query Q is a triple < G, LP, D, where G is the query goal, LP is a logic program without function symbols, and D is a set of facts, possibly stored as tuples of a relational database. The answers of Q are all facts that can be inferred from LP ∪ D and unify with G. A logic query is bound if some argument of the query goal is a constant; it is canonical strongly linear (a CSL query) if LP contains exactly one recursive rule and this rule is linear, i.e., only one recursive predicate occurs in its body. In this paper, the problem of finding the answers of a bound CSL query is studied with the aim of comparing for efficiency some well-known methods for implementing logic queries: the eager method, the counting method, and the magic-set method. It is shown that the above methods can be expressed as algorithms for finding particular paths in a directed graph associated to the query. Within this graphical formalism, a worst-case complexity analysis of the three methods is performed. It turns out that the counting method has the best upper bound for noncyclic queries. On the other hand, since the counting method is not safe if queries are cyclic, the method is extended to safely implement this kind of queries as well

Dynamic Data Structures for Series Parallel Digraphs

We consider the problem of dynamically maintaining general series parallel directed acyclic graphs (GSP dags), two-terminal series parallel directed acyclic graphs (TTSP dags) and looped series parallel directed graphs (looped SP digraphs). We present data structures for updating (by both inserting and deleting either a group of edges or vertices) GSP dags, TTSP clags and looped SP digraphs of m edges and n vertices in O( log n) worst-case time. The time required to check whether there is a path between two given vertices is O(log n), while a path of length k can be traced out in O(k + log n) time. For GSP and TTSP dags, our data structures are able to report a regular expression describing all the paths between two vertices x and y in O(h + log n), where h ≤ n is the total number of vertices which are contained in paths from x to y. Although GSP dags can have as many as O(n2) edges, we use an implicit representation which requires only O(n) space. Motivations for studying dynamic graphs arise in several areas, such as communication networks, Incremental compilation environments and the design of very high level languages, while the dynamic maintenance of series parallel graphs is also relevant in reducible flow diagrams

A Systematization of Cybersecurity Regulations, Standards and Guidelines for the Healthcare Sector

The growing adoption of IT solutions in the healthcare sector is leading to a steady increase in the number of cybersecurity incidents. As a result, organizations worldwide have introduced regulations, standards, and best practices to address cybersecurity and data protection issues in this sector. However, the application of this large corpus of documents presents operational difficulties, and operators continue to lag behind in resilience to cyber attacks. This paper contributes a systematization of the significant cybersecurity documents relevant to the healthcare sector. We collected the 49 most significant documents and used the NIST cybersecurity framework to categorize key information and support the implementation of cybersecurity measures.Comment: 14 page