Self Organizing Ambient Control Space – An Ambient Network Architecture for Dynamic Network Interconnection Peter Kersch
[email protected]
Robert Szabo
[email protected]
Zoltan Lajos Kis
[email protected]
Budapest University of Technology and Economics 1117, Budapest Magyar Tudosok korutja 2.
ABSTRACT
1. INTRODUCTION
One of the major challenges in ambient networking is to provide interworking between heterogeneous and dynamically changing networks. This paper presents a novel network and system architecture enabling network self-organization and dynamic network composition. The proposed network architecture is based on a hierarchical overlay network model, where components of the overlays can also be overlays themselves. This introduces a self-contained network architecture argued to suit ambient networking. The network architecture is discussed together with the rules or composition principles that enforce an attracting tree structure to the hierarchical overlays. Besides the network architecture the major components of the system architecture is also presented involving the naming and addressing scheme and handling of network management data. 1
Nowadays mobile networking technologies have infiltrated into everyday life. Besides radio access infrastructures like GSM, UMTS, WiFi hotspots, etc, dynamically formed ad hoc type networks (personal area networks, body area networks, etc.) are also emerging. These different kinds of networks should be able to interconnect at different interworking levels depending on the level of trust between them. Omnipresence of networking and dynamic interworking between different networking technologies opens a new area in telecommunications entitled ubiquitous or ambient networking. A flexible ambient networking technology supporting statical and dynamical (either self-organizing) network composition and automated configuration and maintenance would be beneficial. This technology should handle different kinds of policies and restrictions to enable information protection and should be able to advertise and manage any kind of service offered by nodes (e.g printing service) or by groups of nodes (e.g. redundant data storage, processing capacity). The static nature of currently used networking technologies (especially regarding network composition) and network policies currently hinder automated creation of dynamic networks and automated interworking of these existing networks. Dynamic network composition and decomposition requires continuous reconfiguration of the network and continuous maintenance of the offered services. These frequent changes should not require user intervention; they should happen automatically based on higher level user intentions. To address these requirements, this paper presents a self organizing network architecture developed in the context of the EU sponsored Ambient Networks project. In Ambient Networks [6], nodes self-organize themselves into networks and networks of networks (all called AN). Nodes of an AN share a common distributed control space called ACS (Ambient Control Space) and these logical networks can be seen as hierarchical overlays created for management and control tasks. Overlays are formed by taking into account neighbor proximities and policies [11] and dynamically adapt the logical network structure to changes in physical network topology. The maintenance of such a hierarchical overlay network provides a scalable framework for configuration management, performance management, service advertisement and discovery – all of these are indispensable for efficient network interworking. The rest of the paper is structured as follows: Section 2 introduces related work for self-organizing networks and network composition. Section 3 proposes a network architec-
Categories and Subject Descriptors C.2.1 [Computer-Communication Networks]: Network Architecture and Design—Distributed networks, Network Topology, Wireless Communication
General Terms Algorithms, Management, Design
Keywords Self organizing networks, network management, overlay networks, network composition 1 This document is a byproduct of the Ambient Networks Project, partially funded by the European Commission under its Sixth Framework Program. The views and conclusions contained herein are those of the authors and should not be interpreted as necessarily representing the official policies or endorsements, either expressed or implied, of the Ambient Networks Project or the European Commission.
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ture based on a hierarchical overlay network model and composition primitives. Section 4 presents the necessary system architecture to provide self-organization and dynamic network composition. Finally Section 5 concludes the paper.
2.
Hierarchical overlay network
RELATED WORK
Self organization and dynamic network composition are key requirements in ambient networking. While dynamic network composition [3] is a very recent concept developed in the Ambient Networks [6] project, self organization has been extensively researched in the peer-to-peer networks and mobile ad hoc networks fields during the last few years. Several distributed algorithms have been proposed to self-organize such systems into a scalable network structure. Most of these proposals could be classified into two categories: clustering and overlay networks.
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Figure 1: Example hierarchical overlay network
2.1 Clustering Clustering is a commonly used mechanism in ad hoc environments to create a hierarchical structure over a flat physical topology, thus making the system more scalable. Most clustering algorithms self-organize nodes in clusters so that each node is assigned to a clusterhead elected among them. Clustering structure is dynamically reorganized, self-adapting to changes in physical topology. During cluster creation, two main factors are taken into account: physical topology and a preference value to become clusterhead. Most algorithms create clusters so that cluster members are direct neighbors [2] or are at most from ”d” hop distance [1] from their clusterhead. Although cluster maintenance involves communication overhead, it has been shown to be polylogarithmic in the node count under most circumstances [10]. Clustering has already proven to be useful for routing, medium access control, address assignment and other control plane tasks. However while considering to use it for managing composable networks, the following problems should be addressed: • Most clustering schemes do not allow more then 2 hierarchy levels, causing scalability problems in very large networks • Clustering do not take into account network management information (ex. policies) to create network structure and restricts cluster radius to 1 or ”d” hops • Current clustering algorithms do not consider nodes with multiple network interfaces, although it is frequent in real ambient network scenarios
the overlay network structure, data requests are always forwarded hop by hop to the node nearest to the location of the actual piece of data. Scalability of these search algorithms is achieved by using overlay network structures having a logarithmic diameter. Although DHTs realize self organizing overlay networks, they have been optimized for efficient data lookup in distributed networks and thus cannot be used to provide scalable network structures for composable networks. The most important limitations of DHT overlays are the followings: • Merging of previously separate DHTs is very problematic – it implies repartitioning of the whole key space – thus network composition would be difficult • Most DHTs have a flat structure or the number of hierarchy levels is limited
3. NETWORK ARCHITECTURE In our distributed Ambient Control Space architecture, self organization and dynamic network composition are based on a novel hierarchical overlay model. Unlike most clustering algorithms and peer-to-peer overlay networks, the proposed hierarchical overlay structure may have an unlimited number of hierarchy levels and provides primitives for dynamic network composition. The overlay structure is tightly related to the underlaying physical network topology. However – unlike for most clustering models – the overlay topology is also highly influenced by network management information like policies.
2.2 Overlay Networks
3.1 Hierarchical ACS Overlays
Overlay networks are logical (virtual) networks created on top of a physical network topology. Overlays can be either fixed or dynamically changing and self-configuring. The most widely used self organizing overlays are Distributed Hash Tables (DHT) used in peer-to-peer networks becoming extremely popular during the last few years. Examples are Chord [9], CAN [7], Pastry [8], Tapestry [12]. DHTs are used for efficient lookup of data stored by nodes of a large distributed network. Each piece of data in the network is mapped with a key/value pair. Each node of the network joins the overlay network of the DHT and is responsible for mapping one part of the key space. Using
The basic components of the hierarchical overlay model are overlay nodes called peers, super-peers and overlays. On one hand an overlay is a set of peers belonging to one Ambient Network. On the other hand, overlays extend the AN with virtual connections – network – between its constructed peers. The AN itself is defined by the common control space shared by its peers. Each overlay elects a super-peer to represent the overlay towards the outside world. It is important to note that this super-peer is solely responsible for negotiations with other overlays and has no other special privileges within its overlay. Super-peers may also form overlays at higher hierarchy
levels hereby creating a hierarchical overlay network structure. Fig. 1 shows an example network topology and its associated hierarchical overlay structure atop this physical network. Peers are marked by colored ellipses and superpeers are drawn by thicker lines. All peers belonging to the same overlay are filled with the color of their super-peers. As shown in Fig. 1, the hierarchical overlay structure can be described by a complex graph model. Vertices of this graph are overlay nodes and neighboring overlay nodes of the same overlay are connected by a non-directed edge if there is a neighborhood relationship between them. Besides these neighborhood links, there are also directed edges pointing from super-peer nodes to the parent overlay node at the next upper level. Neighborhood relationship between overlay nodes is determined by hierarchical overlay structure and physical connectivity. Two nodes of the same overlay are neighbors if it is possible to select at least two leaf nodes from the overlay sub-tree of the two nodes so that they are physical neighbors. In the example network in Fig. 1, overlay nodes A and E are neighbors at the topmost level, because nodes C and D from the sub tree of A (A, B, C, D) are physical neighbors with node E from the sub tree of E (E, F, G, H, I). In contrast, nodes A and K at the topmost level are not neighbors because there is not physical connectivity between nodes of sub tree of A and K. Note that neighborhood relationship is only defined between nodes of the same overlay at the same hierarchy level. Another characteristic of the presented hierarchical overlays is that hierarchy levels are not absolute. This means that one cannot assign an absolute hierarchy level index to an overlay (see again Fig. 1, where the top level overlay comprises two peers as 3rd level super-peer and an other one as 2nd level super-peer). However, a bottommost level overlay is defined for all peers.
3.2 Network compositions The hierarchical overlay graph unequivocally determines physical and logical network structure, therefore network self-organization and all network compositions can be described as manipulations on this overlay graph. The behavior and logics of network composition is defined using two main principles: 1. Absorption or gatewaying type of composition decided by peer-to-peer negotiations 2. Bottom-up network composition Principle 1) defines two composition types: absorption and gatewaying. Two networks compose by absorption if they have mutually acceptable policies and can agree on setting up a common ambient control space. Thus two overlays composing by absorption will result in one single overlay represented by one single super-peer (see Fig. 2). This super-peer can be either one of the two former super-peers, but it is also possible to elect a new super-peer from peers of the unified network. If the two networks cannot create a common ambient control space (due to address conflicts, other control space problems or incompatible policy sets, for example), they will compose by gatewaying. During gatewaying type of composition, the two overlays will keep their own separate ACS but an upper level overlay will be created whose members
Figure 2: Absorption composition model
Figure 3: Gatewaying composition model will be the two super-peers (see Fig. 3). The ACS associated with this upper level overlay is responsible for providing and regulating interworking between the to overlays. The number of hierarchy levels in the overlay structure may increase as a result of gatewaying type compositions. Composition between networks having multiple overlay levels is governed by principle 2). When two previously separate networks get in contact, bottommost level overlays will detect each other by neighbor discovery procedures. After the recognition that they belong to different top level overlays, the bottommost level overlays will try to compose. If they can agree on absorption type composition, they complete the absorption procedure. Otherwise, the two superpeers forward composition to the next upper overlay until either the two parties can agree on absorption type composition or the top level overlay is reached. In the former case, the top level overlay of one network will merge into an overlay of the other network at some level as shown in Fig. 4(a). In the latter case, the two networks will compose by gatewaying and the two top level super-peers will create an additional overlay level as show in Fig. 4(b). (Hint: letters above the arrows in Fig. 4 denote the negotiated composition type – A stands for Absorption, G stands for Gatewaying – while the numbers in brackets determine the sequence of composition negotiations2 .) Composition type is decided as a result of peer-to-peer negotiations between the super-peers of the two composing overlays. It is important to note that direct network level communication may not be possible between the two superpeers during composition, thus if they are not direct physical neighbors, all composition messages will be relayed by overlay boundary nodes of bottommost neighboring overlays. When large networks meet, multiple composition processes may be triggered at the same time. While one super-peer may be involved into multiple composition processes at different overlay levels, to avoid inconsistent network states, 2
For simplicity, Fig. 4 uses a reduced overlay model (combined tree-set representation), where connections inside overlays are omitted.
2. should not change too often in order to reduce cost of network maintenance,
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3. reflect somehow the members they are composed of.
G(1)
(a) absorption G(2)
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(b) gatewaying Figure 4: Bottom-up composition principle it is not allowed to participate in multiple compositions on behalf of the same overlay. Until the current composition finishes, other composition requests are waiting in a peroverlay queue. However, before starting a new composition from the queue, the super-peer must reexamine composition conditions. Decomposition is also an integral part of the self-organization framework. It will not be discussed in detail in this paper but it is important to note that decomposition is not the inverse of composition, it is a completely different process.
4.
SYSTEM ARCHITECTURE
4.1 Naming and addressing Naming and addressing is a crucial component in all network architectures and has an impact on the overall operation of the network. Our architecture uses the nowadays so popular “locator/identifier split”, whereby Ambient Networks and the physical AN nodes are identified by their AN IDs and Node IDs respectively. Prior to communication, identifiers are resolved to locators.
Locators A locator (address) identifies the point of attachment to a network (i.e., a network interface – either physical or logical).
Node Identifiers Nodes in Ambient Networks are identified by globally unique permanent cryptographic host identifiers called Peer Identifiers or Peer IDs. Peer IDs are 128 bit long in order to ease eventual migration to the Host Identity Protocol [5]. In fact, HITs (Host Identity Tags) could be directly used as Peer IDs. To enable implementation of future security mechanisms, Peer IDs should be generated by secure one way hash functions from the public key of the host (just in the way it is done in HIP).
Ambient Network Identifiers Network identifiers present more difficulties than host identifiers as they have to satisfy difficult and partly conflicting requirements, namely: 1. being globally unique identifiers,
Requirement 2) is difficult to be met in highly dynamic networks. Network composition makes it even impossible to use permanent network identifiers as every time two previously separate networks merge by absorption, at least one of them must change its network ID. Requirement 3 is also difficult and conflicts with requirement 2). If all the network members are accounted in the AN ID, then frequent member joins and leaves would challenge 2). Therefore, each AN should make an attempt to limit these changes throughout its applied policies. Extreme example could be that only some information regarding the selected super-peer is incorporated into the AN ID.
Addressing When two nodes of the same AN want to communicate (note that a node of an AN might also be an AN) then there must exist direct layer-3 communication paths between them. Therefore the IDs can be resolved to valid locators. This scenario is named intra-AN communication. However, if two ANs must exchange information then PDUs are either routed through the hierarchical overlays, whereas each overlay adheres to the intra-AN procedure, or once the final destination’s locator is known (e.g. after the first PDU exchange) and is top level AN wide valid then direct peerto-peer communication might be used. During a network composition process, AN boundary nodes (overlay boundary nodes) must relay PDU messages between the networks.
4.2 Registries One vital function required by the ACS is a general data registry that enables distributed and transparent storage of management and control information. Because of this generality, the ACS will encounter several kinds of information that can have very dissimilar usage models. Therefore, implementing a general data storage mechanism would not be sufficiently efficient. Instead, one has to classify the information and let the ACS Registry decide what kind of storing mechanism it uses based on the classification of the information. We have identified four main aspects the stored information should be classified by: i) the source and ii) destination of the information, iii) its permanency, and iv) its update/access ratio. The source of the information can be a single peer, or more peers. If more peers are acting as a source, they might update the same information with a more recent version, or provide a part of the information. The destination of an information can be a single peer, or more peers as well. When there are more destinations, the gathering and distribution of the information is the main question. Some information can be permanent, meaning that it is useful for the ACS even after its originator has left the AN, while some are temporary, losing their value when their originator leaves the AN. Based on this classification we found different storage and distribution mechanisms, which used in parallel shall offer a near optimal storage for each and every combination of the above mentioned classes. Distributed hash tables can serve
as a base of the ACS registry, making it possible to introduce an indexing mechanism. Their redundant extensions can also be used for the reliable storage of permanent data. Pattern based messaging[4] can be used for both the distribution and aggregation of ACS-wide data, where actual sources and destinations can be registered into the distributed hash tables. For further optimization, an intelligent caching mechanism can be used, that is a combination of the traditional client-server architecture and the pattern-based broadcasting. The ACS registry, based on preliminary meta-information, and run-time statistics, can decide which storage mechanism to use for a certain information. Because the different functional areas of the control space shall access the ACS registry on a well-defined interface, the actual realization of the registry could be completely hidden, hence being transparent.
5.
CONCLUSION
This article discussed a novel hierarchical overlay architecture, which enables dynamic network composition by selforganizing networks and networks of networks. The overlay system architecture was described with two conceptually different network composition methods: the absorption and the gatewaying. In our view, two networks compose by absorption if they have mutually acceptable policies and can agree on setting up a common control space. This way, one of the two originally distinct networks will dissolve into the other. In all other cases, the two or more networks will compose with gatewaying, when their original control spaces will be retained while a new one is created based on their common sets. However, the location of this new control space will be a virtual network (an overlay), which contains its ancestor networks as nodes. The procedure that manages the composition process is a bottom-up method, which enforces network composition at the possible lowest overlay level. Additionally, a tree structure will be enforced on the hierarchical overlay structure in consideration for the physical topology. Besides, the major components of the system architecture were also discussed like the locator/identifier split introduced by the node and overlay IDs and their requirements on the architecture or the different data registries. Overall, this piece of work is a part of a bigger concept called Ambient Networks[6], where the architecture depicted herein was also prototyped3 by the authors of this article. Detailed numerical analysis for this prototype will be the subject of a follow-up paper in progress.
6.
ADDITIONAL AUTHORS
Additional authors: M´ ark Erdei (Budapest University of Technology and Economics, email:
[email protected]) and Bal´ azs Kov´ acs (Budapest University of Technology and Economics, email:
[email protected]).
3
Peer-to-peer Ambient control space Prototype – PAP
7. REFERENCES [1] Amis, A. D., Prakash, R., Vuong, T. H., and Huynh, D. T. Max-min d-cluster formation in wireless ad hoc networks. In Proc. of INFOCOM 2000 (2000). [2] Basagni, S. Distributed and mobility-adaptive clustering for multimedia support in multi-hop wireless networks. In Proc. of VTC 1999 (1999). [3] Kappler, C., Mendes, P., Prehofer, C., Poeyhoenen, P., and Zhou, D. A framework for self-organized network composition. In Proc. of 1st International Workshop on Autonomic Communication (2004). [4] Lim, K.-S., and Stadler, R. A navigation pattern for scalable internet management. In Proc. of IEEE/IFIP International Symposium on Integrated Network Management (2001). [5] Moskowitz, R., Nikander, P., Jokela, P., and Henderson, T. Host identity protocol architecture work in progress (draft-moskowitz-hip-arch-06), June 2004. [6] Niebert, N., Schieder, A., Abramowicz, H., Malmgren, G., Sachs, J., Horn, U., Prehofer, C., and Karl, H. Ambient networks: an architecture for communication networks beyond 3g. IEEE Wireless Communications 11, 2 (Apr. 2004), 14–22. [7] Ratnasamy, S., Handley, M., Karp, R., and Shenker, S. A scalable content-addressable network. In Proc. of ACM SIGCOM 2001 (2001). [8] Rowstron, A., and Druschel, P. Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems. In Proc. of IFIP/ACM International Conference on Distributed Systems Platforms 2001 (2001). [9] Stoica, I., Morris, R., Karger, D., Kaashoek, M., and Balakrishnan, H. Chord: A scalable peer to peer lookup service for internet applications. In Proc. of ACM SIGCOM 2001 (2001). [10] Sucec, J., and Marsic, I. Clustering overhead for hierarchical routing in mobile ad hoc networks. In Proc. of INFOCOM 2002 (2002). ´ , R., Kersch, P., Kova ´ cs, B., Simon, C., [11] Szabo Erdei, M., and Wagner, A. Dynamic network composition for ambient networks: a management view. In Proc. of Eurescom Summit 2005 (Apr. 2005). [12] Zhao, B. Y., Kubiatowicz, J., and Joseph, A. D. Tapestry: An infrastructure for fault-tolerant wide-area location and routing, 2001.
