A signaling protocol for service function localization

Current proposals for chaining service functions (SFs) do not address some critical management issues, such as the discovery of SF instances close to IP data paths. This information is crucial for deploying complex services both in large cloud networks, where SFs may be moved or replicated, and in the emerging fog/mobile edge computing systems. For this purpose, in this letter, we propose the distributed off-path signaling protocol. We show the protocol functions and demonstrate its scalability and effectiveness by experimental results

A binary hybrid replication strategy for improving availability and maintaining consistency of data in large scale mobile environments

Data Management in mobile computing environments poses great challenges to the database researchers. One of the important challenges is to provide a data replication solution that maintains the consistency and improves the availability of replicated data. This paper addresses this problem for large scale distributed information systems that operate in mobile environments. Our solution represents a new binary hybrid replication strategy, in terms of its components and approach. The new strategy encompasses two components: replication architecture to provide a solid infrastructure for improving data availability and replication method to transfer data updates in a manner that achieves the consistency of data. The new strategy is a hybrid of both pessimistic and optimistic replication approaches, in order to exploit the features of each. The proposed strategy supports higher data availability and lower rate of inconsistencies as well as supports the mobility of users

Mobile Online Gaming via Resource Sharing

Mobile gaming presents a number of main issues which remain open. These are concerned mainly with connectivity, computational capacities, memory and battery constraints. In this paper, we discuss the design of a fully distributed approach for the support of mobile Multiplayer Online Games (MOGs). In mobile environments, several features might be exploited to enable resource sharing among multiple devices / game consoles owned by different mobile users. We show the advantages of trading computing / networking facilities among mobile players. This operation mode opens a wide number of interesting sharing scenarios, thus promoting the deployment of novel mobile online games. In particular, once mobile nodes make their resource available for the community, it becomes possible to distribute the software modules that compose the game engine. This allows to distribute the workload for the game advancement management. We claim that resource sharing is in unison with the idea of ludic activity that is behind MOGs. Hence, such schemes can be profitably employed in these contexts.Comment: Proceedings of 3nd ICST/CREATE-NET Workshop on DIstributed SImulation and Online gaming (DISIO 2012). In conjunction with SIMUTools 2012. Desenzano, Italy, March 2012. ISBN: 978-1-936968-47-

Maintaining cache consistency in mobile computing environments.

by Leung Wing Man.Thesis (M.Phil.)--Chinese University of Hong Kong, 1996.Includes bibliographical references (leaves 73-75).Abstract --- p.iAcknowledgements --- p.iiiChapter 1 --- Introduction --- p.1Chapter 2 --- Background --- p.7Chapter 2.1 --- What is Mobile Computing? --- p.7Chapter 2.1.1 --- Applications of Mobile Computing --- p.8Chapter 2.1.2 --- New Challenges of Mobile Computing --- p.9Chapter 2.2 --- Related Work --- p.12Chapter 2.2.1 --- Lazy Replicated File Service --- p.12Chapter 2.2.2 --- Dividing the Database into Clusters --- p.14Chapter 2.2.3 --- Applying Causal Consistency --- p.15Chapter 2.3 --- Summary --- p.16Chapter 2.4 --- Serializability and Concurrency Control --- p.17Chapter 3 --- System Model and Suggested Protocol --- p.20Chapter 3.1 --- System Model --- p.20Chapter 3.2 --- Cache Management --- p.21Chapter 3.2.1 --- Version Control Mechanism --- p.22Chapter 3.2.2 --- Cache Consistency --- p.22Chapter 3.2.3 --- Request Data from Servers --- p.25Chapter 3.2.4 --- Invalidation Report --- p.27Chapter 3.2.5 --- Data Broadcasting --- p.30Chapter 4 --- Simulation Study --- p.32Chapter 4.1 --- Physical Queuing Model --- p.32Chapter 4.2 --- Logical System Model --- p.33Chapter 4.3 --- Parameter Setting --- p.34Chapter 4.4 --- The Significance of the Length of Invalidation Range --- p.37Chapter 4.4.1 --- Performance with Different Invalidation Range --- p.38Chapter 4.4.2 --- Increasing the Update Frequency --- p.40Chapter 4.4.3 --- Impact of Piggybacking Popular Data --- p.41Chapter 4.4.4 --- Increasing the Disconnection Period --- p.42Chapter 4.5 --- Comparison of the Proposed Protocol with the Amnesic Terminal Protocol --- p.44Chapter 4.5.1 --- Setting a Short Timeout Period --- p.45Chapter 4.5.2 --- Extending the Timeout Period --- p.46Chapter 4.5.3 --- Increasing the Frequency of Temporary Disconnection --- p.48Chapter 4.5.4 --- Increasing the Frequency of Crossing Boundaries --- p.49Chapter 4.6 --- Evaluate the Performance Gain with Piggybacking Message --- p.50Chapter 4.6.1 --- Adding Piggybacking Messages --- p.51Chapter 4.6.2 --- Reducing the Number of Popular Data --- p.52Chapter 4.6.3 --- Increasing the Frequency of Updates --- p.53Chapter 4.7 --- Behaviour of the Proposed Protocol --- p.54Chapter 4.7.1 --- Finding Maximum Number of Mobile Computers --- p.54Chapter 4.7.2 --- Interchanging the Frequency of Read-Only and Update Transactions --- p.55Chapter 5 --- Partially Replicated Database System --- p.57Chapter 5.1 --- Proposed Amendments --- p.57Chapter 5.1.1 --- Not Cache Partially Replicated Data ( Method 1 ) --- p.58Chapter 5.1.2 --- Drop Partially Replicated Data ( Method 2 ) --- p.59Chapter 5.1.3 --- Attaching Server-List ( Method 3 ) --- p.59Chapter 5.2 --- Experiments and Interpretation --- p.60Chapter 5.2.1 --- Partially Replicated Data with High Accessing Probability --- p.61Chapter 5.2.2 --- Reducing the Cache Size --- p.64Chapter 5.2.3 --- Partially Replicated Data with Low Accessing Probability --- p.65Chapter 6 --- Conclusions and Future Work --- p.70Chapter 6.1 --- Future Work --- p.72Bibliography --- p.73Chapter A --- Version Control Mechanism for Servers --- p.7

Smart PIN: utility-based replication and delivery of multimedia content to mobile users in wireless networks

Next generation wireless networks rely on heterogeneous connectivity technologies to support various rich media services such as personal information storage, file sharing and multimedia streaming. Due to users’ mobility and dynamic characteristics of wireless networks, data availability in collaborating devices is a critical issue. In this context Smart PIN was proposed as a personal information network which focuses on performance of delivery and cost efficiency. Smart PIN uses a novel data replication scheme based on individual and overall system utility to best balance the requirements for static data and multimedia content delivery with variable device availability due to user mobility. Simulations show improved results in comparison with other general purpose data replication schemes in terms of data availability

Location based mobile computing - a tuplespace perspective

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2006 IOS PressLocation based or "context aware" computing is becoming increasingly recognized as a vital part of a mobile computing environment. As a consequence, the need for location-management middleware is widely recognized and actively researched. Location-management is frequently offered to the application through a "location API" (e.g. JSR 179) where the mobile unit can find out its own location as coordinates or as "building, floor, room" values. It is then up to the application to map the coordinates into a set of localized variables, e.g. direction to the nearest bookshop or the local timezone. It is the opinion of the authors that a localization API should be more transparent and more integrated: The localized values should be handed to the application directly, and the API for doing so should be the same as the general storage mechanisms. Our proposed middleware for location and context management is built on top of Mobispace. Mobispace is a distributed tuplespace made for mobile units (J2me) where replication between local replicas takes place with a central server (over GPRS) or with other mobile units (using Bluetooth). Since a Bluetooth connection indicates physical proximity to another node, a set of stationary nodes may distribute locality information over Bluetooth connections, and this information may be retrieved through the ordinary tuplespace API. Besides the integration with the general framework for communication and coordination the middleware offers straightforward answers to questions like: Where is node X located? Which nodes are near me? What is the trace of node Y