Related Works. 11.1 Should the Subcontractor’s performance depend in any way on the proper performance of another person, for example, a consultant or another contractor, the Subcontractor must take all reasonable steps to enquire into and discover any defects in such performance and the Subcontractor must promptly provide a written report to Savcor ART relating to any defects it discovers.
Related Works. The number of nodes in a fully secure network can be increased by using multiple key spaces. In [14], ω key spaces are generated and each node is given a sub-set of τ randomly chosen keys from ω. After deployment, nodes discover their common keys and use the Xxxx’x scheme to form pairwise keys. The scheme uses a similar idea to the probabilistic scheme of Eschenaeur-Gligor [3] where nodes are given a random set of keys from a global key space. In these schemes the aim is to achieve full connectivity, but not necessarily complete connectivity like a full mesh. Another approach also uses Xxxx’x scheme with multiple key spaces to improve resistance to the Xxxxx attack [15]. In [16], the scheme for a clustered topology is proposed. Here, the cluster-heads implement the Xxxx’x scheme to derive pairwise keys among themselves. Non cluster-head nodes do not implement the Xxxx’x scheme. Instead, they store a pre-computed secret key Ki for use with a clus- ter head. Prior to deployment, the base station computes the pairwise keys of this node with a certain number of associated cluster-heads. These are then combined into a secret key Ki and stored in the node, together with the identities (IDs) of the associated cluster-heads. When a node needs to establish a secure link with a physical cluster-head, − it sends its own ID and the IDs of its associated cluster- heads. The physical cluster-head forwards the node’s ID to the associated cluster-heads to compute the pairwise keys using Xxxx’x scheme and thereby derives the secret key Ki. In this way, non-cluster head nodes store minimum keying material and do not need to perform any key computation computation. Instead, these are delegated to the cluster heads which carry the additional load of communicating with other cluster heads to derive the key with a non cluster-head node. The network size would still be limited to the (m 1) nodes for a fully secure network. Since cluster-heads establish pairwise keys among themselves using the basic Xxxx’x scheme, the key size and memory requirements, and network size would still be limited to the original scheme.
Related Works. Arbor will provide to Comshare all Related Works owned and developed by Arbor. If a Related Work is developed by a third party and Arbor retains for itself or obtains from the third party, as the case may be, the right to distribute the Related Work to Arbor's customers and distributors, Arbor will use reasonable commercial efforts to obtain or retain the right to provide the Related Work to Comshare for distribution by Comshare under this License Agreement. In such event, Arbor agrees that it will not withhold or encourage any third party to withhold from Arbor the right to relicense the Related Work to Comshare; provided, however, that Arbor does not guarantee that it will be able to retain or obtain such right for Comshare. Notwithstanding the foregoing and by way of limitation, the Parties agree that the rights granted by Arbor to Comshare hereunder shall in no event be greater than the rights granted to or retained by Arbor with respect to the Related Works. In addition, and notwithstanding anything to the contrary herein, (i) with respect to any Related Work owned by a third party, Arbor makes no different representations or warranties to Comshare than those provided by the third party to Arbor and (ii) with respect to any Related Work owned or developed by a third party, Arbor undertakes no obligation of support or maintenance greater than that provided by Arbor to any of its other distributors. In the event that Arbor does retain or obtain rights for Comshare with respect to any Related Work of a third party, Comshare shall pay Arbor an additional royalty as described in Section I(E) of Exhibit D to the License Agreement.
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Related Works. In [8] we have presented a multicoordinated consen- sus protocol (MCC) that extends Fast Paxos [26], with its fast and classic modes. The protocol can switch be- tween classic, fast, and multicoordinated modes in run- time. This feature allows the protocol to be deployed in many different environments and to adapt to changes therein during the execution. It is also an important tool in the study of agreement protocols, by using the right combination of round types and recovery technique, our protocol emulates most consensus protocols that we are aware of. In [9] we have shown the use of the multicoordi- nated mode in solving generic broadcast and discussed its relation to generalized consensus. We reviewed the mul- ticoordinated execution mode in Section 2.5 and MCC in Section 3. In this paper we tackled the problem of efficiently reaching agreement in a network organized as groups of agents. Our solution is an extension of the Collision- Fast Paxos protocol [37], which does not consider groups. For the reader’s convenience we explained CFPaxos in Section 4.2. The same problem, agreement in groups of agents, was studied by Kooh and Xxxxxx [21]. Their hi- erarchical consensus algorithm recursively agrees on pro- posals over a multilevel tree of agents. More specifically, in their protocol each set of agents in a given level of the same branch of the tree constitute a group. From the leaves to the root, agents in the same group agree on a value to be their proposal on the upper level, until they have agreed on a single value at the root of the tree. The cost of such an approach depends on the choice of consensus algorithm used inside each group. There are two main differences between Kooh and Xxxxxx’x work and ours. First, our protocol is better suited for applica- tions that need to agree on all proposals, not just a sin- gle one. This is is the case, for example, when solving atomic broadcast; solutions based on consensus require each command proposed but not decided to be proposed again in a new consensus instance. Because our protocols solve M-Consensus instead, all proposals may be part of a single decision. Second, in Kooh and Xxxxxx’x protocol, agents are replicated using consensus: an instance is used to agree on each state change. In our approach, we let the coor- dinators in each quorum diverge and only use consensus to recover from failures. The price we pay is in terms of messages sent from the group—since each coordina- tor may be in a different...
Related Works. Since the presence of foundational Xxxxxx-Xxxxxxx (DH) protocol [12], several other protocols have been proposed for the group case. The original idea of extending the 2-party DH scheme to the multi-party setting dates back to the classical paper of Ingemarsson [16]. Following their work, Xxxxxxx et al. [22, 23, 24] proposed a family of protocols known as Group Xxxxxx- Xxxxxxx (GDH.1, GDH.2, GDH.3). In these protocols, the last group member serves as a controller and performs most of the computation, therefore, it needs more energy compared with other group members. Owning to the limitation of the nodes energy, the GDH protocol family is not suitable for the Ad-hoc networks. Perrig [21] proposed a tree-based key agreement scheme. After that, Xxx et al. [18] extended the work of [21] to design a Tree-Based Group Xxxxxx- Xxxxxxx (TGDH) protocol. Compared with GDH protocols, it scales down the number of exponentiations and received messages required by the last group member to avoid excessive computational and communication costs required by one node. But TGDH protocol still requires each group member to perform large modular exponentiations and transmit/receive long messages. So the TGDH protocol is also inadequate for Ad-hoc networks. After the work in [4, 9, 25] many other scholars have done abundant related research. However, fairly few research deals with provably-secure group key agreement in a concrete and realistic setting. It is only recently that [20], has presented the first group key agreement scheme proven secure in a well-defined security model. Ng et al. [20] incorporated the identity based cryptosystem with bilinear map and broadcast encryption scheme to construct a secure communication scheme for MANETs. In their scheme, the group members do not perform any message exchanges during the generation process of a group key. However, its security relies on the random oracles. It has been shown that when the random oracles are instantiated with concrete hash functions, the resulting scheme may not be secure [3, 10]. Then, Zhang et al. [26] designed a new scheme which is proved secure in the standard model rather than the random oracles model. Unfortunately, those schemes suffer from long ciphertexts, i.e., the secret message broadcasted to the users will grow linearly with the number of receivers. With the increment of network scale, the shortcoming mentioned above will lead to even serious problems.
Related Works. The Semantic Web was introduced by Xxx Xxxxxxx-Xxx for Dec/31, 2000 June 30, 2008 2000-2008 Africa 4,514,400 51,065,630 1,031.2 % Asia 114,304,000 578,538,257 406.1 % Europe 105,096,093 384,633,765 266.0 % Middle East North America 3,284,800 108,096,800 41,939,200 248,241,969 1,176.8 % 129.6 % America/Caribbean Oceania / Australia 18,068,919 7,620,480 139,009,209 20,204,331 669.3 % 165.1 % WORLD TOTAL 360,985,492 1,463,632,361 305.5 % World Regions Internet Users Internet Usage, Usage Growth the first time in one of his speeches in 1998 as an extension to the current web [3]. He described the different versions of the Semantic Web architecture in 2000 [4], 2003 [5], 2005[6], 2006 [7]. Fensel is one of the main contributors in the Semantic Web field discussed the Semantic Web and the languages associated with its architecture in 2000 [8], while in 2002, he describeed OIL and its relation to OWL and the future capabilities of OWL [9]. Fensel was not the only scientist who made great efforts in this area, but there are Xxx Xxxxxxxx [10], Xxxxx-Xxxxxxxxx [11] and Xxxxxx [12] also participated in this domain. There is still a long way for the full vision for the Semantic Web and the full implementation of it [13] [14].
Related Works. This paper offers an approach to technically con- verge the quality-related ontologies of service, expe- rience, and business as introduced in (Xxx Xxxxxxx, 2001; Xxxxxx and Xxxxxxx-Xxxxxx, 2006). Most other authors address technical perspectives on SLA in SOA. From the IT architecture point of view, authors deal with SLA descriptions of performance modelling (Xxxxxxx, 2008), SLA-driven development (Xxxxxxxxx et al., 2009) or dependability through- out the life cycle (Xxxxxxxxx and Xxxxx, 2010). In operations management SLA are mostly enforced through an distribute-and-enforce tactic. By (Xxx et al., 2008; Xxxxxxxx and Xxxxxxxxxx, 2008; Xxxx et al., 2009; Xxxxxxxxx and Xxxxxxxx, 2008) highly detailed SLAs are defined, distributed and then en- forced on each member of a service cascade. The complexity to manage such approaches increases with the complexity of the given cascade. (Xxxxxxxxx and Xxxxxxxxxx, 2008) decouples SLA operations man- agement from the complexity of a service cascade. This paper presents a similar approach and advances it by embedding BSLA in a whole life cycle concept (Xxxxxxxx and Xxxxxxx, 2010). Technical operations is focused on the technical monitoring of technical re- source thresholds. Three types can be distinguished: active, passive and agent-based (Xxxxx and Xxxxxxxx, 2010). Other authors propose the workflow monitor- ing of business process workloads. It is focused on the workflow state rather than underlying technical mea- surements (Ou et al., 2008). In contrast, (Xxxxx et al., 2008) aims to provide a non-intrusive workflow mon- Xxxxxxxx B., X. Xxxxxxx A., X. Xxxxx R. and Xxxxxxx X.. AGREEING ON AND CONTROLLING SERVICE LEVELS IN SERVICE-ORIENTED ARCHITECTURES. DOI: 10.5220/0003871702670270 In Proceedings of the 2nd International Conference on Cloud Computing and Services Science (CLOSER-2012), pages 267-270 ISBN: 978-989-8565-05-1 Copyright Oc 2012 SCITEPRESS (Science and Technology Publications, Lda.) 267 CLOSER 2012 - 2nd International Conference on Cloud Computing and Services Science itoring approach combined with active SLA manage- ment. This paper broadens this approach to incorpo- rate technical monitoring data and address general IT services based on IP networks.
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Related Works. A. Bio Hashing Biometric is a widely used verification parameter which offers numerous advantages over conventional authentication procedures. Password in addition with smart card are one of them. In addition to that, Biometric is known to be a property which varies on individual users and at the same time it is unable to be replaced. Therefore, the leakage of specific biometric data is an intense risk for the authentication. Various schemes have designed to protect biometric template [25], [26]. Bio-Hasing [27], [28] is a procedure to preserve the privacy of the biometric schemes. In general, the bio-hasing function is declared as BH(K, B). Here, K is a secret parameter shared between user and server. B is the fingerprint of the user. The generation of bio-hasing value is done by comparison between the inner product of the random vector generated form the K and B. In the time of verification, user inputs Bj, performs BH(K, Bj) and send the value to the server. Server calculates BH(K, B) and checks that with the received parameter. If BH(K, B) = BH(K, Bj), then it is confirmed that the sender is a legitimate user.
