Adapting Asynchronous Messaging Middleware to Ad Hoc Networking Mirco Musolesi Cecilia Mascolo Stephen Hailes Dept. of Computer Science University College London MPAC’04

Outline Motivation Background EMMA Current research directions A few ideas for a research roadmap

Motivation Our research goals: Enabling communication in ad hoc networks environments also in presence of disconnections is a hard problem Providing support for the development of distributed applications in these environments Not only a pure theoretical problem, but also practical communication among disconnected communities in poor areas of the world indoor communication interplanetary communication

Motivation In presence of disconnections, synchronous communication mechanisms are not sufficient Asynchronous communication seems a suitable paradigm for mobile ad hoc network settings characterised by frequent disconnections and network partition

Challenges Not only the classic issues of distributed environments but also: Frequent disconnections Limited resources Topology changes Temporary network partitions Heterogeneous mobile devices Different possible deployment scenarios (and consequently different requirements) …

Middleware solutions for ad hoc environments The use of middleware solutions is an effective choice since by adopting them it is possible: to hide the complexity of the underlying networks to deal with the increasing heterogeneity of the devices (laptops, mobile phones, PDAs, sensors, etc.) to design a set of primitives for the adaptation and the configuration of the system

Message oriented middleware for ad hoc environments Starting from these considerations, message oriented middleware based on asynchronous communication mechanism seems a good solution to provide a support for communication also in presence of intermittently connected clouds of hosts Based on the same abstractions of systems for fixed networks, but many additional design issues

Existing middleware systems Many examples of middleware for mobile computing for communication also in the case of intermittent disconnections: Tuple based (i.e., LIME) Sharing of complex data structures (i.e., XMIDDLE) Message oriented middleware for mobile computing: Academic projects: Pronto, Mobile JMS, STEAM, etc. Industrial products: WebSphere MQ EveryPlace, Broadbeam ExpressQ, SoftWired IBus Mobile, etc. However, they do not support pure ad hoc network environment with intermittent connectivity!

EMMA Message oriented middleware for mobile ad hoc networks environments Adaptation of JMS Implementation of both point to point publish/subscribe models Message delivery based on a pure epidemic routing protocol in case of disconnections Based on a different levels of priority for a smart use of buffers

Epidemic-style routing M M M M M M M M M M M M M M M M M M M M M M

Point to point model Queues positioned on a certain number of hosts Queues advertised using the epidemic mechanism If a host is in reach, the message is delivered immediately If a host is not currently in reach, the epidemic style routing is used

Publish-subscribe model Delivery mechanisms based on an epidemic style routing protocol in case of disconnections as in the point to point model Single message with multiple recipients, instead of multiple messages with multiple recipients. In order to delete the other possible replicas around the networks, we exploit acknowledgment messages Adaptation of the semantics of durable and non durable subscriptions

Adaptation of the JMS Message Model Implementation of a subset of the JMS Message Model specification with a different semantics Definition of persistent and non persistent messages Support for messages with different priorities Expiration time used to free space in the buffers

Evaluation of EMMA We have implemented a prototype of our platform using the J2ME Personal Profile The size of the executable is about 250KB including the JMS 1.1 jar file We have tested our prototype on HP IPaq PDAs running Linux and on a number of laptops with the same network interface interconnected with WaveLan. We also evaluated the middleware platform using the OMNET++ discrete event simulator in order to have some simulation results considering scenario composed of a realistic number of hosts.

Simulation parameters Number of hosts: 16/24/32 Simulation area: 1 Km x 1 Km Propagation model: free space Antenna type: omni-directional Transmission range (radius): 200 m Mobility model: clustered random way point Number of clouds: 4 Cloud area: 200 m x 200 m Node speed: 1-3 m/s (randomly generated) Cloud speed: 1-2 m/s (randomly generated) Number of messages sent: 100 Number of recipients (pub/sub): 80% of the number of hosts Max number of hops: 15 Message buffer size: 10 to 100 Routing table size: 20 entries Max distance: 15 Max allowed delay time: 4 minutes

EMMA performance Point to point model (scenario with 32 hosts): delivery ratio of persistent and non persistent messages vs buffer size. Point to point model (scenario with 32 hosts): delivery ratio of persistent and not persistent messages vs population density.

EMMA performance Publish-Subscribe model (scenario with 32 hosts: delivery ratio distribution of persistent messages with different priorities Publish-subscribe model (scenario with 32 hosts): delivery ratio distribution of persistent messages vs buffer size.

Limitations of EMMA Epidemic algorithms are efficient in terms of delivery ratio and delay time but they are really expensive from a resource consumption point of view Discovery process not optimised Queues are not replicated No adaptation Limited set of primitives

Towards a new middleware platform EMMA is our initial effort; we are currently working towards the definition of a new middleware Substitution of the epidemic protocol with a more optimised and adaptive Context-Aware Routing protocol (CAR) Definition of a new set of primitives Support for geocasting

Context-aware middleware for ad hoc networking Exploitation of context information for the optimisation of the delivery process in terms of resource consumption (memory, battery, etc.) Design of prediction mechanisms based on the evaluation of the history of context information (mobility, co-location, battery level, etc.) Replication mechanisms in accordance with the level of required reliability

Cross-layering Current trend in mobile ad hoc networking We think that it is possible to extend this methodology to the design of middleware and applications Optimisation and adaptation of the system can be realised by the integration of the network level software components in the middleware platform.

A few ideas for a roadmap for ad hoc networks middleware research Many open issues or problems not explored sufficiently in depth : Design of adaptive and autonomic systems Self-optimising systems Self-healing systems... Positioning and replication of data and entities Auto-configuration Exploitation of the properties of the underlying network Cross-layering based design Security

Conclusions Cross-layering is a promising methodology for the design of middleware solutions for mobile ad hoc computing EMMA is a first example of a platform for asynchronous messaging in ad hoc networks designed using a cross-layering approach Necessity of new mechanisms for optimisation and context adaptation in such a dynamic environment

Questions Mirco Musolesi Dept. of Computer Science, UCL