The last hop of global notification delivery to mobile users. Matching preferences, context, and device constraints.

Events injected by publishers into a publish/subscribe system may reach users through a variety of devices: a stationary desktop, a laptop, a mobile phone, etc. We argue that the "last hop" -- from the network to the output device -- has unique properties, owing to the mobile nature of these devices, and as such demands special consideration. In particular, user's preferences and location may limit what should be forwarded to a device. Furthermore, technological constraints, such as network bandwidth availability and battery power, suggest that the decision when to forward messages is also important for optimizing user's experience. We describe a new publish/subscribe system with volume-limiting mechanisms and explain how user preferences, context, and device constraints can be accommodated in such a system. Notably, based on results of simulations, we propose a simple algorithm for low-cost "prefetching" of notifications to mobile devices in cases when network bandwidth is insufficient

Automatic subscriptions in publish-subscribe systems

In this paper, we describe how to automate the process of subscribing to complex publish-subscribe systems. We present a proof-of-concept prototype, in which we analyze Web browsing history to generate zero-click subscriptions to Web feeds and video news stories. Our experience so far indicates that user attention data is a promising source of data for automating the subscription process

Minimizing unwanted traffic in a global messaging system. Spam, denial-of-service-attacks, and edacious subscribers

The main purpose of this paper is to illuminate two types of unwanted traffic in a publish/subscribe system -- malicious (spam, DoS attacks) and vain (unused events) -- and suggest a general mechanism for minimizing their effects. We do this by augmenting the classic publish/subscribe interface with volume-limiting parameters -- a combination of attributes assigned to events by publishers and thresholds specified by subscribers -- and consider the implications of this interface on the unwanted traffic and on the routing infrastructure. Notably, we observe that this mechanism can minimize unwanted traffic without total access control if the routing substrate supports two properties: flow control and routing integrity

Managing self-inflicted nondeterminism

this paper we focus on the application level. A wrapper technique can be used for other layers [1

Application Scheduling on the Information Power Grid

One of the compelling reasons for developing the Information Power Grid (IPG) is to provide a platform for more rapid development and execution of simulations and other resource-intensive applications. However, the IPG will ultimately not be successful unless users and application developers can achieve execution performance for their codes. In this paper, we describe a performance-efficient approach to scheduling applications in dynamic multiple-user distributed environments such as the IPG. This approach provides the basis for application scheduling agents called {\bf AppLeS}. We describe the AppLeS methodology and discuss the lessons learned from the development of AppLeS for a variety of distributed applications. In addition, we describe an AppLeS-in-progress currently being developed for NASA's INS2D code, a distributed "parameter sweep" application.Pre-2018 CSE ID: CS2000-064

Application Scheduling on the Information Power Grid

One of the compelling reasons for developing the Information Power Grid (IPG) is to provide a platform for more rapid development and execution of simulations and other resource-intensive applications. However, the IPG will ultimately not be successful unless users and application developers can achieve execution performance for their codes. In this paper, we describe a performance-efficient approach to scheduling applications in dynamic multiple-user distributed environments such as the IPG. This approach provides the basis for application scheduling agents called {\bf AppLeS}. We describe the AppLeS methodology and discuss the lessons learned from the development of AppLeS for a variety of distributed applications. In addition, we describe an AppLeS-in-progress currently being developed for NASA's INS2D code, a distributed "parameter sweep" application.Pre-2018 CSE ID: CS2000-064

Heuristics for Scheduling Parameter Sweep Applications in Grid Environments

The computational Grid provides a promising platform for the efficient execution of parameter sweep applications over very large parameter spaces. Scheduling such applications is challenging because target resources are heterogeneous, because their load and availability varies dynamically, and because tasks may share common data files. In this paper, we propose a scheduling algorithm for parameter sweep applications on the Grid. We consider standard heuristics for task/host assignment (Max-min, Min-min, Sufferage), and we propose an extension of Sufferage called XSufferage. Using simulation, we demonstrate 3 results: 1) that XSufferage can take advantage of file sharing to achieve better performance than the other heuristics under a wide variety of load conditions, 2) that it is possible to characterize the environments under which different heuristics perform best, and 3) that it is possible to characterize the performance of different heuristics under the (realistic) assumption of varying accuracy of performance estimations.Pre-2018 CSE ID: CS1999-063

Automatic subscriptions in publish-subscribe systems

In this paper, we describe how to automate the process of subscribing to complex publish-subscribe systems. We present a proof-of-concept prototype, in which we analyze Web browsing history to generate zero-click subscriptions to Web feeds and video news stories. Our experience so far indicates that user attention data is a promising source of data for automating the subscription process.

Using Simulation to Evaluate Scheduling Heuristics for a Class of Applications in Grid Environments

Fast networks have made it possible to aggregate distributed CPU, memory, and storage resources into Grids that can deliver considerable performance. However, achieving performance on such systems requires good performance prediction which is usually difficult due to their dynamic and heterogeneous nature. This is especially true for parallel applications whose performance is highly dependent upon the efficient coordination of their constituent components (e.g. computation and data). The goal of the AppLeS project is to develop application-level scheduling agents that provide mechanisms for automatically scheduling individual applications on production heterogeneous systems. AppLeS agents utilize the Network Weather Service (NWS) to monitor and forecast the varying performance of resources potentially usable by their applications. Each AppLeS uses static and dynamic application and system information to select viable resource configurations and evaluate their potential performance. The AppLeS then interacts with the appropriate resource management system to implement the application\'s network transfers and computational tasks. The next generation of AppLeS agents aims at providing templates that can be used for scheduling classes of structurally similar applications. In this document we introduce a template for scheduling Parameter Sweep applications (application consisting of \\em large number of independent tasks, with possible input data sharing). We have designed a general scheduling algorithm that can adapt to Grid environments and use a variety of strategies and heuristics to assign tasks and data to resources. In order to evaluate and compare those heuristics we have built a simulator as part of the template. The simulator makes it possible to rapidly conduct large numbers of experiments in a variety of environments. Our starting point was to use widely accepted heuristics that have been proposed in the litterature and venture improvements given our Grid and application model. This document presents the implementation of our simulator and explains how it will be used to obtain new research results in the field of Grid scheduling