Process migration is the act of transferring a process between two machines. It enables dynamic load distribution, fault resilience, eased system administration, and data access locality. Despite these goals and ongoing research efforts, migration has not achieved widespread use. With the increasing deployment of distributed systems in general, and distributed operating systems in particular, process migration is again receiving more attention in both research and product development. As high-performance facilities shift from supercomputers to networks of workstations, and with the ever-increasing role of the World Wide Web, we expect migration to play a more important role and eventually to be widely adopted.This survey reviews the field of process migration by summarizing the key concepts and giving an overview of the most important implementations. Design and implementation issues of process migration are analyzed in general, and then revisited for each of the case studies described: MOSIX, Sprite, Mach, and Load Sharing Facility. The benefits and drawbacks of process migration depend on the details of implementation and, therefore, this paper focuses on practical matters. This survey will help in understanding the potentials of process migration and why it has not caught on.

Process migration

Process migration is the act of transferring a process between two machines. It enables dynamic load distribution, fault resilience, eased system administration, and data access locality. Despite these goals and ongoing research efforts, migration has not achieved widespread use. With the increasing deployment of distributed systems in general, and distributed operating systems in particular, process migration is again receiving more attention in both research and product development. As high-performance facilities shift from supercomputers to networks of workstations, and with the ever-increasing role of the World Wide Web, we expect migration to play a more important role and eventually to be widely adopted.
This survey reviews the field of process migration by summarizing the key concepts and giving an overview of the most important implementations. Design and implementation issues of process migration are analyzed in general, and then revisited for each of the case studies described: MOSIX, Sprite, Mach, and Load Sharing Facility. The benefits and drawbacks of process migration depend on the details of implementation and, therefore, this paper focuses on practical matters. This survey will help in understanding the potentials of process migration and why it has not caught on.

Bayes theory is provably optimal whenever all the sensor sources are contributing information at a single Bayesian level of abstraction. Often, however, this is not the case. Shafer-Dempster reasoning is a generalization of Bayes reasoning that offers a way to combine uncertain information from disparate sensor sources with different levels of abstraction. Shafer-Dempster logic is discussed and described, and realistic examples are provided of its use drawn from the field of multisensor target identification systems and on simulating its operation.

Shafer-dempster reasoning with applications to multisensor target identification systems

The processor allocation problem is addressed in the context of the parallelization of a finite element modeling program on a processor mesh. A heuristic two-step, graph-based mapping scheme with polynomial-time complexity is developed: 1) initial generation of a graph partition for nearest-neighbor mapping of the finite element graph onto the processor graph, and, 2) a heuristic boundary refinement procedure to incrementally alter the initial partition for improved load balancing among the processors. The effectiveness of the approach is gaged both by estimation using a model with empirically determined parameters, as well as implementation and experimental measurement on a 16 node hypercube parallel computer.

Nearest-Neighbor Mapping of Finite Element Graphs onto Processor Meshes

A semidistributed approach is given for load balancing in large parallel and distributed systems which is different from the conventional centralized and fully distributed approaches. The proposed strategy uses a two-level hierarchical control by partitioning the interconnection structure of a distributed or multiprocessor system into independent symmetric regions (spheres) centered at some control points. The central points, called schedulers, optimally schedule tasks within their spheres and maintain state information with low overhead. The authors consider interconnection structures belonging to a number of families of distance transitive graphs for evaluation, and, using their algebraic characteristics, show that identification of spheres and their scheduling points is in general an NP-complete problem. An efficient solution for this problem is presented by making exclusive use of a combinatorial structure known as the Hadamard matrix. The performance of the proposed strategy has been evaluated and compared with an efficient fully distributed strategy through an extensive simulation study. The proposed strategy yielded much better results. >

/pdf/semi-distributed-load-balancing-for-massively-parallel-3einsecswx.pdf

Semi-distributed load balancing for massively parallel multicomputer systems

Fowler's Seventh Law for military systems [1] states: "Be wary of proposals for synergistic systems. Most of the time when you try to make 2 + 2 = 5, you end up with 3-and sometimes 1.9." We attempt to approach the broad issues of IFFN (identification, friend, foe, neutral) of military targets via the techniques of NCTR (noncooperative target recognition), coupled with the systems approach called "sensor fusion." Although the overall style of the paper is that of a tutorial, many of the results presented are original. In all cases where we make political obsrvations, they represent our personal opinions.

NCTR Plus Sensor Fusion Equals IFFN or can Two Plus Two Equal Five

Digital design with standard MSI and LSI

Task Allocation Heuristics for Distributed Computing Systems.

A linear error-sampled control system can be designed to track inputs of the form tkwith zero error in finite time.

Deadbeat response to parabolic inputs with minimum-squared error restrictions on ramp and step responses

The most common approach to microcomputer software development is to first assemble the program on the microcomputer system or cross-assemble it on a larger computer; then debug the program in the microcomputer or simulate it on another computer; and finally burn the program into a ROM or PROM.

John L. Pokoski

Papers

NCTR Plus Sensor Fusion Equals IFFN or can Two Plus Two Equal Five

Digital design with standard MSI and LSI

Task Allocation Heuristics for Distributed Computing Systems.

Deadbeat response to parabolic inputs with minimum-squared error restrictions on ramp and step responses

A Software Development System for Microcomputers