27,518 research outputs found
The Relative Power of Composite Loop Agreement Tasks
Loop agreement is a family of wait-free tasks that includes set agreement and
simplex agreement, and was used to prove the undecidability of wait-free
solvability of distributed tasks by read/write memory. Herlihy and Rajsbaum
defined the algebraic signature of a loop agreement task, which consists of a
group and a distinguished element. They used the algebraic signature to
characterize the relative power of loop agreement tasks. In particular, they
showed that one task implements another exactly when there is a homomorphism
between their respective signatures sending one distinguished element to the
other. In this paper, we extend the previous result by defining the composition
of multiple loop agreement tasks to create a new one with the same combined
power. We generalize the original algebraic characterization of relative power
to compositions of tasks. In this way, we can think of loop agreement tasks in
terms of their basic building blocks. We also investigate a category-theoretic
perspective of loop agreement by defining a category of loops, showing that the
algebraic signature is a functor, and proving that our definition of task
composition is the "correct" one, in a categorical sense.Comment: 18 page
Byzantine Approximate Agreement on Graphs
Consider a distributed system with n processors out of which f can be Byzantine faulty. In the approximate agreement task, each processor i receives an input value x_i and has to decide on an output value y_i such that
1) the output values are in the convex hull of the non-faulty processors\u27 input values,
2) the output values are within distance d of each other.
Classically, the values are assumed to be from an m-dimensional Euclidean space, where m >= 1.
In this work, we study the task in a discrete setting, where input values with some structure expressible as a graph. Namely, the input values are vertices of a finite graph G and the goal is to output vertices that are within distance d of each other in G, but still remain in the graph-induced convex hull of the input values. For d=0, the task reduces to consensus and cannot be solved with a deterministic algorithm in an asynchronous system even with a single crash fault. For any d >= 1, we show that the task is solvable in asynchronous systems when G is chordal and n > (omega+1)f, where omega is the clique number of G. In addition, we give the first Byzantine-tolerant algorithm for a variant of lattice agreement. For synchronous systems, we show tight resilience bounds for the exact variants of these and related tasks over a large class of combinatorial structures
Wait-Free Solvability of Equality Negation Tasks
We introduce a family of tasks for n processes, as a generalization of the two process equality negation task of Lo and Hadzilacos (SICOMP 2000). Each process starts the computation with a private input value taken from a finite set of possible inputs. After communicating with the other processes using immediate snapshots, the process must decide on a binary output value, 0 or 1. The specification of the task is the following: in an execution, if the set of input values is large enough, the processes should agree on the same output; if the set of inputs is small enough, the processes should disagree; and in-between these two cases, any output is allowed. Formally, this specification depends on two threshold parameters k and l, with k<l, indicating when the cardinality of the set of inputs becomes "small" or "large", respectively. We study the solvability of this task depending on those two parameters. First, we show that the task is solvable whenever k+2 <= l. For the remaining cases (l = k+1), we use various combinatorial topology techniques to obtain two impossibility results: the task is unsolvable if either k <= n/2 or n-k is odd. The remaining cases are still open
CSP channels for CAN-bus connected embedded control systems
Closed loop control system typically contains multitude of sensors and actuators operated simultaneously. So they are parallel and distributed in its essence. But when mapping this parallelism to software, lot of obstacles concerning multithreading communication and synchronization issues arise. To overcome this problem, the CT kernel/library based on CSP algebra has been developed. This project (TES.5410) is about developing communication extension to the CT library to make it applicable in distributed systems. Since the library is tailored for control systems, properties and requirements of control systems are taken into special consideration. Applicability of existing middleware solutions is examined. A comparison of applicable fieldbus protocols is done in order to determine most suitable ones and CAN fieldbus is chosen to be first fieldbus used. Brief overview of CSP and existing CSP based libraries is given. Middleware architecture is proposed along with few novel ideas
On-line replacement of program modules using AdaPT
One purpose of our research is the investigation of the effectiveness and expressiveness of AdaPT(1), a set of language extensions to Ada 83, for distributed systems. As a part of that effort, we are now investigating the subject of replacing, e.g., upgrading, software modules while the software system remains in operation. The AdaPT language extension provide a good basis for this investigation for several reasons: (1) they include the concept of specific, self-contained program modules which can be manipulated; (2) support for program configuration is included in the language; and (3) although the discussion will be in terms of the AdaPT language, the AdaPT to Ada 83 conversion methodology being developed as another part of this project will provide a basis for the application of our findings to Ada 83 systems. The purpose of this investigation is to explore the basic mechanisms to the replacement process. Thus, while replacement in the presence of real-time deadlines, heterogeneous systems, and unreliable networks is certainly a topic of interest, we will first gain an understanding of the basic processes in the absence of such concerns. The extension of the replacement process to more complex situations can be made later. This report will establish an overview of the on-line upgrade problem, and present a taxonomy of the various aspects of the replacement process
Human-Machine Collaborative Optimization via Apprenticeship Scheduling
Coordinating agents to complete a set of tasks with intercoupled temporal and
resource constraints is computationally challenging, yet human domain experts
can solve these difficult scheduling problems using paradigms learned through
years of apprenticeship. A process for manually codifying this domain knowledge
within a computational framework is necessary to scale beyond the
``single-expert, single-trainee" apprenticeship model. However, human domain
experts often have difficulty describing their decision-making processes,
causing the codification of this knowledge to become laborious. We propose a
new approach for capturing domain-expert heuristics through a pairwise ranking
formulation. Our approach is model-free and does not require enumerating or
iterating through a large state space. We empirically demonstrate that this
approach accurately learns multifaceted heuristics on a synthetic data set
incorporating job-shop scheduling and vehicle routing problems, as well as on
two real-world data sets consisting of demonstrations of experts solving a
weapon-to-target assignment problem and a hospital resource allocation problem.
We also demonstrate that policies learned from human scheduling demonstration
via apprenticeship learning can substantially improve the efficiency of a
branch-and-bound search for an optimal schedule. We employ this human-machine
collaborative optimization technique on a variant of the weapon-to-target
assignment problem. We demonstrate that this technique generates solutions
substantially superior to those produced by human domain experts at a rate up
to 9.5 times faster than an optimization approach and can be applied to
optimally solve problems twice as complex as those solved by a human
demonstrator.Comment: Portions of this paper were published in the Proceedings of the
International Joint Conference on Artificial Intelligence (IJCAI) in 2016 and
in the Proceedings of Robotics: Science and Systems (RSS) in 2016. The paper
consists of 50 pages with 11 figures and 4 table
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