utilize the hypernetwork theory as the foundation for the design of future ... network and more applications and services will be enabled by the network. Clearly ...
A Design Principle for Future High-Speed Networks Kejie Lu1 , Tao Zhang2 , Shengli Fu3 , Yi Qian1 , Ashwin Gumaste4 , and S.-Q. Zheng5 1 2
Department of Electrical and Computer Engineering, University of Puerto Rico at Mayag¨uez, Mayag¨uez, PR 00681. School of Engineering and Computing Sciences, New York Institute of Technology, Old Westbury, NY 11568, USA. 3 Department of Electrical Engineering, University of North Texas, Denton, TX 76207, USA. 4 School of Information Technology, Indian Institute of Technology, Powai, Mumbai 400-076, India 5 Department of Computer Science, the University of Texas at Dallas, Richardson, TX 75083, USA.
2) Reliability: The current IP-based network architecture can only provide packet rerouting, which is not adequate to quickly respond to failures in the network. Moreover, this weakness is amplified in the core network due to the high data rate. 3) Security. In the IP-based core network, it is virtually impossible to distinguish malicious traffic from legitimate traffic because the packets are all mixed together and the source addresses can be spoofed. 4) Cost. Because of the high data rate, the cost for developing and deploying advanced technologies is high. Consequently, carriers may be reluctant to upgrade their system for providing better services. To address the scalability issue, we propose a novel network design principle that can lead to a more scalable, robust, secure, and efficient network infrastructure. The main idea of the principle is to utilize the hypernetwork theory and applications [2], [3]. The key innovation of the hypernetwork is its capacity to provide connectivity by establishing hyperchannels (or hyperedges, hyperarcs, hyperlinks), each of which may consist of more than two nodes, in the network. Within a hyperchannel, connectivity of nodes can be achieved by multiple access schemes. Moreover, multiple hyperchannels can be used to establish a hyperpath, which can further improve the connectivity. In the rest of this paper, we will first discuss the scalability issue of the current Internet architecture in Section II, followed by the basics of hypernetwork in Section III. We will then elaborate on the detail design for optical networks and wireless networks, in Section IV and Section V, respectively. Finally, we conclude this paper in Section VI.
Abstract— In this paper, we discuss the design philosophy for future high-speed networks. We argue that the fundamental issue for a communication network is to provide connectivity, which means that one node in the network shall be able to send data to another node within a certain amount of time. To provide connectivity in high-speed networks, the key challenge is the scalability issue, which has not been fully addressed in most existing network architectures. To address this challenge, we propose to utilize the hypernetwork theory as the foundation for the design of future high-speed networks. We then use optical network and high-speed wireless network as two examples to illustrate and justify the hypernetwork-based network architecture. Index Terms— Network architecture, high-speed, hypernetwork, hyperchannel
I. I NTRODUCTION In the past twenty years, we have witnessed significant growth of the Internet. In the future, the scale of the Internet will keep increasing: more entities will be connected to the network and more applications and services will be enabled by the network. Clearly, high-speed networks will become essential to the future Internet. Although many architectures have been proposed for highspeed network in the literature, we observe that a key challenge, the scalability issue, has not been fully addressed. To understand this problem, it is important to appreciate that providing connectivity is the fundamental characteristic of a communication network, where connectivity means that one node in the network shall be able to send data to another node within a certain amount of time. With this basic concept, we can further understand other issues, such as the addressing, routing, bandwidth, and quality-of-service (QoS). These issues, in fact, are the challenges faced by the current Internet architecture, as pointed out in [1]. With the dramatic growth of the Internet, both the number of users and the amount of traffic have increased drastically, causing a number of scalability problems, all of which are related to the connectivity. 1) Performance: In the current Internet, traffic from different end users will first be partitioned into small packets, which are then aggregated at edge networks before being forwarded into the core network. Because of the aggregation, the data rate of the traffic is extremely high in the core network. Consequently, it is very difficult to perform the basic packet forwarding function, let alone the more complex controls on bandwidth, delay, and other quality-of-service (QoS) demands.
II. T HE S CALABILITY I SSUE OF T HE C URRENT I NTERNET A RCHITECTURE In this section, we will use the current Internet architecture to discuss the scalability issue. To understand the scalability problem, we shall first analyze some fundamentals of the Internet. Essentially, the current Internet is a packet-based networking system that can only provide best-effort service. Within the system, each packet will be stored and forwarded individually at each node, i.e., router, in the network. Conceptually, routers in the network are organized in a hierarchical manner. For simplicity, we can consider a two-level hierarchy, in which there are two types of routers, i.e., core routers and edge routers. In this architecture, edge routers are responsible
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for aggregating the traffic from end users, and core routers inter-connect with one another to form a backbone of the Internet. With the growth of the Internet, the data rate of the core network keeps increasing in order to provide enough bandwidth and connectivity for the increasing number of users and applications. Consequently, the following scalability issues are becoming more and more serious. First, because of the aggregation, the data rate of the traffic is extremely high in the core network. In fact, with the increase of the data rate, even the basic forwarding function is very difficult to implement in the core router [4]. Consequently, it is very difficult to provide guaranteed bandwidth, delay, and other QoS requirements in the core network. In practice, the core network either does not provide any QoS (i.e., besteffort), or it provides QoS only in a relative sense, namely, via DiffServ. In terms of reliability, the current Internet architecture can only provide packet rerouting, which is not adequate to quickly respond to failures in the network. In addition, this weakness is amplified in the core network due to the high data rate. Moreover, in the core network, it is virtually impossible to distinguish malicious traffic from legitimate traffic because the packets are all mixed together. For instance, let us consider a major threat to Internet-based service: the distribute denial-ofservice (DDoS) attack, in which attackers can launch attacks from thousands of compromised computers in the network. Typically, the source addresses of the attack packets are forged. This means that a network operator on the victim side cannot efficiently respond to such attack. Finally, because of the extremely high data rate, the cost for developing and deploying advanced technologies is also high. Consequently, carriers may be reluctant to upgrade their systems to provide better services. To address the aforementioned scalability issues, we believe that the hypergraph theory can provide a better solution. For instance, if sufficient connectivity can be provided by a hypergraph-based networks, then the number of high-data-rate routers can be significantly reduced. Moreover, a great amount of energy can also be saved if part of the routing and switching functionalities can be performed in a hyperchannel, in which the store-and-forward operations can be eliminated. In the next section, we will provide background for hypernetwork.
Fig. 1.
An example of hypernetwork.
Compared to regular graph, the key feature of hypergraph is that a hyperchannel can provide connectivity for multiple nodes in the hyperedge. Consequently, a connection in existing network architectures, which are based on regular graph, can provide connectivity only for the two end nodes. By contrast, one hyperchannel can support connectivity amongst all its nodes. A simple example of a hypernetwork is given in Fig. 1, which illustrates the Metro subway system in Washington DC. In this network, differently colored lines represent different hyperchannels. Within a hyperchannel, people can access any nodes following a predefined schedule. Moreover, one can move from one location in the network to another through hyperpaths, which are connections between multiple hyperchannels (lines). Obviously, such a network system is quite efficient and, intuitively, the performance of such a system can be further improved if hyperchannels (and consequently, hyperpaths) can be reconfigured according to needs. Another advantage of the Metro system is that it can provide guaranteed delay, which is very important for most passengers. In contrast, in the case of a conventional road network traversed by automobiles, the delay is not guaranteed (especially at rush hours) since one may need to wait in one’s car at each intersection, which is very similar to the scenario of storeand-forward packet switching. IV. H YPERNETWORK -BASED O PTICAL N ETWORK D ESIGN A. Existing Optical Switching Paradigms
III. BASICS OF H YPERNETWORK According to [3], a hypergraph H = (V, E) consists of a set V = {v1 , v2 , · · · , vN } of nodes, and a set E = {e1 , e2 , · · · , eM } of hyperedges such that each edge ej is a non-empty subset of V and the union of all ej is V . The size sH (ej ) of a hyperedge ej in H is the number of nodes it contains. Clearly, if the size of each hyperedge is 2, then H is a conventional graph. A hypernetwork is then defined as a network whose underlying structure is a hypergraph H, in which each node vi corresponds to a unique network node and each hyperedge ej is a hyperchannel that connects all the nodes of ej . In other words, a hyperchannel can support communications amongst any set of nodes that is in the hyperedge. The topology TH (ej ) of a hyperedge ej in H represents the connectivity of nodes within the hyperedge ej .
In the past decade, significant progress has been made in optical communications technologies. With the advance of Dense Wavelength Division Multiplexing (DWDM) [5], a single optical fiber can now support a more than 2-Terabit per second data rate. To fully utilize such a high data rate, alloptical networks, in which data can be delivered transparently in the optical domain, have been proposed. In the literature, there are mainly three approaches to optical switching: 1) wavelength-routed or optical circuit switching (OCS) [6], 2) optical burst switching (OBS) [7], and 3) optical packet switching (OPS) [9], [10]. Comparing existing optical networking technologies, we first observe that OCS is the most practical solution because it does not require immature technologies such as high-speed
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optical switching fabric. This is mainly because the duration of a lightpath is much longer than the duration for setting up a lightpath. On the other hand, we can find that OCS has a serious scalability issue because a lightpath will occupy an entire wavelength. Supposing the number of nodes in the network is N , we notice that the possible connection requests are on the order of N 2 . On the other hand, the possible number of simultaneous lightpaths is on the order of N , because each fiber can only provide a limited number of wavelengths. With the increase of N , the scalability problem will become more and more serious. One simple solution for addressing the scalability issues is to decrease the duration of the lightpath, which is exactly the same philosophy that is applied in OBS and OPS. However, such network architectures require 1) high-speed optical addressing, 2) optical buffering, 3) high-speed wavelength conversion, and 4) high-speed optical switching and forwarding, which are technologies still in nascent stages of development. Another possible solution in the literature is to combine a logical topology design and traffic grooming, with the help of electronic switching. The logical topology can be considered as an overlay network above an OCS network that can provide connectivity. Traffic grooming schemes, on the other hand, aim at improving the bandwidth efficiency of a lightpath [11]. For this solution, we note that the scalability and efficiency issues of the optical network have not been fully addressed. For example, suppose we have a chain topology with five consecutive nodes: A, B, C, D, and E; two lightpaths (1) between node A and node E and (2) between node C and node E have been established previously; and we need to support a new traffic flow between node A and node C. In this example, we can utilize the existing lightpaths of AE and CE for the traffic between node A and node C. However, this approach is not optimal because the best way is to forward traffic directly from A to C via B. To address the scalability issue in optical network, a hypernetwork-based approach, namely, the SMART architecture, has been proposed in [3], in which the authors designed a novel switch architecture that can efficiently establish hyperchannels. For the example above, if a hyperchannel is establish to link the five nodes, then this hyperchannel can support the connectivity requirements of any subset of the nodes, including unicast, multicast, and broadcast. Similar to lightpath in OCS, the hyperchannel will be kept for a rather long duration, which implies that there is no need to deploy expensive high-speed switching elements. Similar to the Washington DC Metro system, each node in the hyperchannel can access the resource through a schedule. In this manner, the bandwidth and delay can also be guaranteed.
new components of the SMART node architecture are as the following: 1) A Drop-and-continue/drop switching element (DC/D SE) for each incoming wavelength. As a switching element, DC/D SE has one input (connected to an incoming wavelength) and two outputs, which will be connected to 1) the OTS, and 2) the optical-electronic (OE) converter, respectively. Depending on the set of outputs, DC/D SE can have three states: 1) “drop-andcontinue” (to both outputs), 2) “drop” (to OE converter only), and 3) “pass” (to OTS only). 2) A Electrical router or switch (ERS) that can switch data in the electronic domain. The input traffic of ERS includes traffic from local networks and traffic dropped by the DC/D SE. The output traffic of the ERS will be forward to either the local networks or the optical network. C. How The SMART Network Works? 1) The Usage of OTS and Wavelength Converter: With the node architecture, the OTS and wavelength converters, are mainly responsible for establishing hyperchannels. Once a hyperchannel has been established, it can be maintained for a rather long duration, such as hours or even longer. In this manner, we can significantly reduce the frequency of switching in the optical domain, which is a major design criterion. 2) The Usage of DC/D SEs and CA/A Couplers: Within a hyperchannel, DC/D SEs and CA/A couplers can be utilized to support diverse traffic. Supposing that the time-division multiplexing (TDM) scheme is used, we can separate the time horizon into frames, each of which consists of a number of time slots. Obviously, we need to set the state of the DC/D SE in each end node to “drop”. To support different traffic demands, we have two options. In the first option, we can set the DC/D SE in every intermediate node to the “dropand-continue” state and keep it unchanged unless the traffic demands are changed. In the second one, we can change the states of DC/D SEs in only a subset of intermediate nodes, at the beginning of each time slot. For the example that we discussed in Section IV-A, we can establish a hyperchannel for nodes A, B, C, D, and E. To support the traffic between A and E, and between C and E, what we need to do is to assign two time slots in one frame. In the first time slot, node A send traffic to node E; in the second time slot, node C sends traffic to node E. Now suppose we also need to support the traffic between nodes A and C. If the first scheme is used, where we cannot change the state of any DC/D SE, then we only need to allocate three time slots in the frame. If the second scheme is used, then we can keep the two time slots in a frame, and we only need to switch the state of the DC/D SE on node C between “drop” and “pass”, at the beginning of each time slot. Clearly, if the state is “drop”, both traffic from node A to node C and traffic from node C to E can be supported in the same slot. Comparing the two schemes above, we note that the second scheme can achieve better wavelength reuse, at the cost of a longer guard time between adjacent slots and the need for dynamic adjustment of the state of DC/D SE.
B. Node Architecture in the SMART Network To enable hyperchannels in optical networks, a node architecture has been developed in [3]. Similar to a typical optical switch, the SMART node architecture consists of DeMultiplexers (for each input fiber), Multiplexers (for each output fiber), optical switching element (denoted as Optical transit switch (OTS) in [3]), control unit, etc. The major
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wireless environment, such as cooperative communications, network coding, directional antenna, and beam-forming. • Cooperative Communications: The main idea of cooperative communications [12] is to enable the cooperation of nodes in the network. With cooperative communications, the throughput between a sender and a receiver can be significantly improved with the help of other nodes, who can contribute their power, processing capability, and communication bandwidth. Most of the cooperation protocols in the literature consist of two phases. In phase I, the source will broadcast the information to the relay nodes. In phase II, the relay nodes will forward the received information to the destination in a collaborative way. The approaches to address the noisy information received by the relay nodes can be grouped into two categories: amplify-and-forward (AF) and decode-andforward (DF) [12]. In the AF mode, the relay node can only process the received signal linearly before retransmitting it. No demodulation or decoding of the received signal is performed in this case. In the DF mode, the relay nodes are allowed to decode and re-encode the message before retransmission. Although there are a number of studies in the literature, we note that most of them have not emphasized the overhead issue, i.e., how to coordinate many nodes in a wireless scenario. • Network Coding: In general, the main functionality of nodes in existing communication networks can be considered as a “copy” operation. For example, at a certain router in a packet-based network, a unicast packet will be copied to a certain output port with delay; and a multicast packet may be copied to two or more output ports with delay. Now let the input packets of a flow be a sequence of symbols, xk (t), where parameter k represents the sequence number and t denotes the time. We can see that the output of the router, for the given flow, can be expressed as
3) The Control and Management of Hyperchannel: In SMART network, one of the most important issues is how to setup hyperchannels. From the discussion above, we can observe that a hyperchannel in SMART network is similar to a lightpath in OCS networks in that both of them are the basic units in providing connectivity. Therefore, the establishment of hyperchannel can be similar to that of the lightpath. In other words, the hyperchannel can be established and released in a centralized manner, or can be done distributed, depending on the application scenarios. Unlike the lightpath, which can only provide connectivity for the two end nodes, a hyperchannel can provide connectivity for multiple nodes in the hyperchannel. Consequently, a hyperchannel can be considered as a shared medium, which is shared by nodes attached to it. To efficiently utilize the capacity of hyperchannel, bandwidth allocation among contending nodes must be managed. In general, there are two types of scheduling methods for contention resolution and bandwidth allocation: 1) fixed schedule and 2) dynamic multiple access coordination. Fixed schedule is useful when the traffic is static and TDM is a nature choice for fixed schedule. Dynamic multiple access, on the other hand, is suitable for dynamic traffic. To accommodate dynamic requests, the medium can be allocated by a coordinator in the hyperchannel, or can be allocated in a distributed manner. D. Highlights of The Design In the above discussion, we have illustrated a hypernetworkbased optical network design, i.e., the SMART architecture. Due to limited space, below we briefly summarize the key features of the SMART design. 1) In the SMART architecture, hyperchannel is the building block for providing connectivity. 2) A hyperchannel can provide connectivity for all the nodes in it, which can efficiently solve the scalability issue. 3) The SMART architecture is connectivity-centric, not IPcentric. In other words, the SMART is not packet based, which will significantly reduce the overhead in highspeed IP networks. 4) In a hyperchannel, buffer is not necessary and thus there is no unpredictable queueing delay at intermediate nodes. Therefore, the hyperchannel can provide guaranteed delay. However, some delay may occur at edge nodes, which implies that the edge node shall be able to store the data temporarily. Nevertheless, the storage shall not a big issue because the capacity of electronic memory, given the same cost, will keep increasing in the foreseeable future.
yk (t) = αk xk (t − dk ), where dk is the delay for the k-th packet and αk can be 1 or 0, which means that the packet passed the router or was dropped, respectively. By comparison, if network coding is used, then the output of the router can be expressed as yk (t) = f [xk (t), xk−1 (t), · · · , xk−M (t)], which means that the output packet is a function, denoted as f (· · ·), of some packets that have been received previously. In the literature, most existing studies on network coding are for wired network. Recently, [13] and [14] provided some interesting network coding design for wireless networks. The authors in [13] studied network coding design for a single multicast connection in both wired and wireless networks. The most important contribution in [13] is that using network coding can optimize the utilization of network resources, which is crucial especially for wireless communications. In addition, the formulation of network coding can significantly simplify
V. H YPERNETWORK -BASED H IGH -S PEED W IRELESS N ETWORK D ESIGN Based on the hypernetwork principle, we can also design a novel high-speed wireless mesh network. One of the main advantages of the design is similar to that of the optical counterpart, the scalability. In addition, the design can also enable and utilize the potential of advanced technologies in
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TABLE I T RANSMISSION IN A HYPERCHANNEL
Slot Slot Slot Slot
1 2 3 4
x y x y
Original (A → B) (C → B) (B → C) (B → A)
Network coding x (A → B) y (C → B) x+y (B → A, C)
To further improve the performance, we can combine cooperative communication with network coding. As illustrated in Table I, both node A and C can transmit their data in the first slot. Therefore, node B cannot decode any of the block individually, but the summation. In the second slot, node B can broadcast the summation to node A and C, which can then try to decode the messages. Compared to the original scheme, our proposed scheme can reduce the number of slots by half and thus can significantly improve the performance of the network, which has been confirmed in our study. Due to limited space, we will present the performance results in our future publication.
Cooperative network coding x (A → B) and y (C → B) x+y (B → A, C)
the network flow problem. For instance, with the traditional approach, the problem for finding the optimum multicast tree, known as the Steiner tree problem, is NP-hard. By comparison, the network coding approach can solve the same problem in polynomial time, given the same constraints and objective as that of the Steiner tree problem. While most existing studies on network coding are focusing on a single multicast connection, an interesting scheme was presented in [14] for multiple unicast connections in typical, IEEE 802.11-based, ad hoc networks.
VI. C ONCLUSIONS In this paper, we have proposed a novel design philosophy for future high-speed networks. In particular, we argue that the fundamental issue for a communication network is to provide connectivity and the key challenge is the scalability issue, which has not been fully addressed in most existing network architectures. To address this challenge, we propose to utilize the hypernetwork theory as the foundation for the design of future high-speed networks. We used both optical network and high-speed wireless network as two examples to illustrate and justify the hypernetwork-based network architecture.
From the discussion above, we can see that both the cooperative communications and network coding can significantly improve the performance of wireless network. However, most existing studies have not consider the coordination overheads in wireless networks, which is distributed in nature. Another observation is that both of them can improve the performance even if the network is not packet-based. To solve the scalability issue in high-speed wireless network and to enable advanced technologies such as cooperative communications and network coding, we propose to design a hypernetwork-based wireless network. In this design, multihop wireless hyperchannel can be established to provide connectivity for its nodes. While the wireless hyperchannel shall have most good features as its optical counterpart, the broadcast nature of wireless communication can be further exploited. For example, consider a simple network scenario that consists of three nodes, A, B, and C, in a chain topology. We assume that node A and C can only exchange messages with node B. Now suppose a hyperchannel has been established and a TDM-based schedule has been pre-determined for supporting static traffic from node A to C and from node C to A, respectively. At a specific instance, node A has a block of data, denoted as x, to be delivered; while node C has a block of data y to be transmitted. With the current network architecture, a total of four (4) time slots are needed to exchange these two blocks of data, as shown in Table I. With network coding, the task can be performed in three slots, as shown in Table I. The key point is that node B can broadcast x + y to node A and C, which still have the information of x and y, respectively. Consequently, these two nodes can decode the message successfully. It is important to note that here the coordination overheads have been minimized due to the establishment of the hyperchannel. In addition, we note that network coding can be utilized even if the network is not packet-based. Moreover, within the hyperchannel, the amount of data that shall be stored in each node can be easily obtained.
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